High Speed Infrared Cameras Enable Demanding Thermal Imaging Applications

Recent developments in cooled mercury cadmium telluride (MCT or HgCdTe) infrared detector technology have made possible the development of high performance infrared cameras for use in a wide variety of demanding thermal imaging applications. These infrared cameras are now available with spectral sensitivity in the shortwave, mid-wave and long-wave spectral bands or alternatively in two bands. In addition, a variety of camera resolutions are available as a result of mid-size and large-size detector arrays and various pixel sizes. Also, camera features now include high frame rate imaging, adjustable exposure time and event triggering enabling the capture of temporal thermal events. Sophisticated processing algorithms are available that result in an expanded dynamic range to avoid saturation and optimize sensitivity. These infrared cameras can be calibrated so that the output digital values correspond to object temperatures. Non-uniformity correction algorithms are included that are independent of exposure time. These performance capabilities and camera features enable a wide range of thermal imaging applications that were previously not possible.

At the heart of the high speed infrared camera is a cooled MCT detector that delivers extraordinary sensitivity and versatility for viewing high speed thermal events.

1. Infrared Spectral Sensitivity Bands

Due to the availability of a variety of MCT detectors, high speed infrared cameras have been designed to operate in several distinct spectral bands. The spectral band can be manipulated by varying the alloy composition of the HgCdTe and the detector set-point temperature. The result is a single band infrared detector with extraordinary quantum efficiency (typically above 70%) and high signal-to-noise ratio able to detect extremely small levels of infrared signal. Single-band MCT detectors typically fall in one of the five nominal spectral bands shown:

• Short-wave infrared (SWIR) cameras - visible to 2.5 micron

• Broad-band infrared (BBIR) cameras - 1.5-5 micron

• Mid-wave infrared (MWIR) cameras - 3-5 micron

• Long-wave infrared (LWIR) cameras - 7-10 micron response

• Very Long Wave (VLWIR) cameras - 7-12 micron response

In addition to cameras that utilize "monospectral" infrared detectors that have a spectral response in one band, new systems are being developed that utilize infrared detectors that have a response in two bands (known as "two color" or dual band). Examples include cameras having a MWIR/LWIR response covering both 3-5 micron and 7-11 micron, or alternatively certain SWIR and MWIR bands, or even two MW sub-bands.

There are a variety of reasons motivating the selection of the spectral band for an infrared camera. For certain applications, the spectral radiance or reflectance of the objects under observation is what determines the best spectral band. These applications include spectroscopy, laser beam viewing, detection and alignment, target signature analysis, phenomenology, cold-object imaging and surveillance in a marine environment.

Additionally, a spectral band may be selected because of the dynamic range concerns. Such an extended dynamic range would not be possible with an infrared camera imaging in the MWIR spectral range. The wide dynamic range performance of the LWIR system is easily explained by comparing the flux in the LWIR band with that in the MWIR band. As calculated from Planck's curve, the distribution of flux due to objects at widely varying temperatures is smaller in the LWIR band than the MWIR band when observing a scene having the same object temperature range. In other words, the LWIR infrared camera can image and measure ambient temperature objects with high sensitivity and resolution and at the same time extremely hot objects (i.e. >2000K). Imaging wide temperature ranges with an MWIR system would have significant challenges because the signal from high temperature objects would need to be drastically attenuated resulting in poor sensitivity for imaging at background temperatures.

2. Image Resolution and Field-of-View

2.1 Detector Arrays and Pixel Sizes

High speed infrared cameras are available having various resolution capabilities due to their use of infrared detectors that have different array and pixel sizes. Applications that do not require high resolution, high speed infrared cameras based on QVGA detectors offer excellent performance. A 320x256 array of 30 micron pixels are known for their extremely wide dynamic range due to the use of relatively large pixels with deep wells, low noise and extraordinarily high sensitivity.

Infrared detector arrays are available in different sizes, the most common are QVGA, VGA and SXGA as shown. The VGA and SXGA arrays have a denser array of pixels and consequently deliver higher resolution. The QVGA is economical and exhibits excellent dynamic range because of large sensitive pixels.

More recently, the technology of smaller pixel pitch has resulted in infrared cameras having detector arrays of 15 micron pitch, delivering some of the most impressive thermal images available today. For higher resolution applications, cameras having larger arrays with smaller pixel pitch deliver images having high contrast and sensitivity. In addition, with smaller pixel pitch, optics can also become smaller further reducing cost.

2.2 Infrared Lens Characteristics

Lenses designed for high speed infrared cameras have their own special properties. Primarily, the most relevant specifications are focal length (field-of-view), F-number (aperture) and resolution.

Focal Length: Lenses are normally identified by their focal length (e.g. 50mm). The field-of-view of a camera and lens combination depends on the focal length of the lens as well as the overall diameter of the detector image area. As the focal length increases (or the detector size decreases), the field of view for that lens will decrease (narrow).

A convenient online field-of-view calculator for a range of high-speed infrared cameras is available online.

In addition to the common focal lengths, infrared close-up lenses are also available that produce high magnification (1X, 2X, 4X) imaging of small objects.

Infrared close-up lenses provide a magnified view of the thermal emission of tiny objects such as electronic components.

F-number: Unlike high speed visible light cameras, objective lenses for infrared cameras that utilize cooled infrared detectors must be designed to be compatible with the internal optical design of the dewar (the cold housing in which the infrared detector FPA is located) because the dewar is designed with a cold stop (or aperture) inside that prevents parasitic radiation from impinging on the detector. Because of the cold stop, the radiation from the camera and lens housing are blocked, infrared radiation that could far exceed that received from the objects under observation. As a result, the infrared energy captured by the detector is primarily due to the object's radiation. The location and size of the exit pupil of the infrared lenses (and the f-number) must be designed to match the location and diameter of the dewar cold stop. (Actually, the lens f-number can always be lower than the effective cold stop f-number, as long as it is designed for the cold stop in the proper position).

Lenses for cameras having cooled infrared detectors need to be specially designed not only for the specific resolution and location of the FPA but also to accommodate for the location and diameter of a cold stop that prevents parasitic radiation from hitting the detector.

Resolution: The modulation transfer function (MTF) of a lens is the characteristic that helps determine the ability of the lens to resolve object details. The image produced by an optical system will be somewhat degraded due to lens aberrations and diffraction. The MTF describes how the contrast of the image varies with the spatial frequency of the image content. As expected, larger objects have relatively high contrast when compared to smaller objects. Normally, low spatial frequencies have an MTF close to 1 (or 100%); as the spatial frequency increases, the MTF eventually drops to zero, the ultimate limit of resolution for a given optical system.

3. High Speed Infrared Camera Features: variable exposure time, frame rate, triggering, radiometry

High speed infrared cameras are ideal for imaging fast-moving thermal objects as well as thermal events that occur in a very short time period, too short for standard 30 Hz infrared cameras to capture precise data. Popular applications include the imaging of airbag deployment, turbine blades analysis, dynamic brake analysis, thermal analysis of projectiles and the study of heating effects of explosives. In each of these situations, high speed infrared cameras are effective tools in performing the necessary analysis of events that are otherwise undetectable. It is because of the high sensitivity of the infrared camera's cooled MCT detector that there is the possibility of capturing high-speed thermal events.

The MCT infrared detector is implemented in a "snapshot" mode where all the pixels simultaneously integrate the thermal radiation from the objects under observation. A frame of pixels can be exposed for a very short interval as short as <1 microsecond to as long as 10 milliseconds. Unlike high speed visible cameras, high speed infrared cameras do not require the use of strobes to view events, so there is no need to synchronize illumination with the pixel integration. The thermal emission from objects under observation is normally sufficient to capture fully-featured images of the object in motion.

Because of the benefits of the high performance MCT detector, as well as the sophistication of the digital image processing, it is possible for today's infrared cameras to perform many of the functions necessary to enable detailed observation and testing of high speed events. As such, it is useful to review the usage of the camera including the effects of variable exposure times, full and sub-window frame rates, dynamic range expansion and event triggering.

3.1 Short exposure times

Selecting the best integration time is usually a compromise between eliminating any motion blur and capturing sufficient energy to produce the desired thermal image. Typically, most objects radiate sufficient energy during short intervals to still produce a very high quality thermal image. The exposure time can be increased to integrate more of the radiated energy until a saturation level is reached, usually several milliseconds. On the other hand, for moving objects or dynamic events, the exposure time must be kept as short as possible to remove motion blur.

Tires running on a dynamometer can be imaged by a high speed infrared camera to determine the thermal heating effects due to simulated braking and cornering.

One relevant application is the study of the thermal characteristics of tires in motion. In this application, by observing tires running at speeds in excess of 150 mph with a high speed infrared camera, researchers can capture detailed temperature data during dynamic tire testing to simulate the loads associated with turning and braking the vehicle. Temperature distributions on the tire can indicate potential problem areas and safety concerns that require redesign. In this application, the exposure time for the infrared camera needs to be sufficiently short in order to remove motion blur that would reduce the resulting spatial resolution of the image sequence. For a desired tire resolution of 5mm, the desired maximum exposure time can be calculated from the geometry of the tire, its size and location with respect to the camera, and with the field-of-view of the infrared lens. The exposure time necessary is determined to be shorter than 28 microseconds. Using a Planck's calculator, one can calculate the signal that would be obtained by the infrared camera adjusted withspecific F-number optics. The result indicates that for an object temperature estimated to be 80°C, an LWIR infrared camera will deliver a signal having 34% of the well-fill, while a MWIR camera will deliver a signal having only 6% well fill. The LWIR camera would be ideal for this tire testing application. The MWIR camera would not perform as well since the signal output in the MW band is much lower requiring either a longer exposure time or other changes in the geometry and resolution of the set-up.

The infrared camera response from imaging a thermal object can be predicted based on the black body characteristics of the object under observation, Planck's law for blackbodies, as well as the detector's responsivity, exposure time, atmospheric and lens transmissivity.

3.2 Variable frame rates for full frame images and sub-windowing

While standard speed infrared cameras normally deliver images at 30 frames/second (with an integration time of 10 ms or longer), high speed infrared cameras are able to deliver many more frames per second. The maximum frame rate for imaging the entire camera array is limited by the exposure time used and the camera's pixel clock frequency. Typically, a 320x256 camera will deliver up to 275 frames/second (for exposure times shorter than 500 microseconds); a 640x512 camera will deliver up to 120 frames/second (for exposure times shorter than 3ms).

The high frame rate capability is highly desirable in many applications when the event occurs in a short amount of time. One example is in airbag deployment testing where the effectiveness and safety are evaluated in order to make design changes that may improve performance. A high speed infrared camera reveals the thermal distribution during the 20-30 ms period of airbag deployment. As a result of the testing, airbag manufacturers have made changes to their designs including the inflation time, fold patterns, tear patterns and inflation volume. Had a standard IR camera been used, it may have only delivered 1 or 2 frames during the initial deployment, and the images would be blurry because the bag would be in motion during the long exposure time.

Airbag effectiveness testing has resulted in the need to make design changes to improve performance. A high speed infrared camera reveals the thermal distribution during the 20-30ms period of airbag deployment. As a result of the testing, airbag manufacturers have made changes to their designs including the inflation time, fold patterns, tear patterns and inflation volume.

Even higher frame rates can be achieved by outputting only portions of the camera's detector array. This is ideal when there are smaller areas of interest in the field-of-view. By observing just "sub-windows" having fewer pixels than the full frame, the frame rates can be increased. Some infrared cameras have minimum sub-window sizes. Commonly, a 320x256 camera has a minimum sub-window size of 64x2 and will output these sub-frames at almost 35Khz, a 640x512 camera has a minimum sub-window size of 128x1 and will output these sub-frame at faster than 3Khz.

Because of the complexity of digital camera synchronization, a frame rate calculator is a convenient tool for determining the maximum frame rate that can be obtained for the various frame sizes.

3.3 Dynamic range expansion

One of the complications of having a very high sensitivity infrared detector is that the overall scene dynamic range will be limited. For example, if a raw count corresponds to 5 mK/digital count, a 14-bit signal range will deliver less than 80 degrees C in dynamic range. This range is further reduced because of pixel non-uniformity. As a consequence, the range of object temperatures that can be viewed in one frame may be too narrow for the application.

To increase the apparent dynamic range, a unique solution can be implemented which allows the user to artificially expand the dynamic range without sacrificing the high sensitivity performance of the camera. (This mode is sometimes called Dynamic Range ExtendIR, DR-X, superframing, multi-IT). When the dynamic range expansion mode is engaged, the camera sequentially captures multiple frames, each frame having a different exposure time. The short sequence includes frames that are highly sensitive (because of long exposure times) and also less sensitive frames for imaging objects at higher temperatures (because of shorter exposure times). For the method to be effective, the overall time for the frame sequence must be short enough to avoid motion blur. If this is the case, then camera software combines the frames into one image frame having the entire dynamic range for the sequence.

As an example, consider the following sequence of images showing the process of mixing a cold fluid to a flask of boiling liquid. If an exposure time was selected based on the full temperature range, the thermal resolution of the cooler objects will be poor. Conversely, if the exposure time is selected to improve the thermal resolution of the cold fluid, the hotter objects may cause saturation. As a result, with dynamic range expansion, multiple integration times can be selected that span the entire scene dynamic range.

Exposure time 110 microseconds / Frames 1,4,7 / Object Temperature Range 65-150 degrees C

Exposure time 600 microseconds / Frames 2,5,8 / Object Temperature Range 35-70 degrees C

Exposure time 1375 microseconds / Frames 3,6,9 / Object Temperature Range 5-40 degrees C

In this example, three exposure times have been selected (1375 microseconds, 600 microseconds, and 110 microseconds) to cover a wide scene temperature. The camera then cycle through each exposure time at the full frame rate. If the camera is operating at 240 frames/second, the first frame will be at the first exposure time, the second frame will be at the second exposure time, the third at the third exposure time. The fourth frame will begin the sequence again at the first exposure time. The system will effectively generate three sequences, three frames apart, each at a rate of 80 frames/second with the three exposures times. Through image processing, the sequential frames can be recombined into one complete sequence making a pixel by pixel determination as to the apparent signal, further increasing the dynamic range. The resulting image is shown below (with a 5-150 degrees C object temperature scale):

The exposure times correspond to different camera sensitivities. In operation, the camera is programmed to select the appropriate exposure time frame by frame. The resulting data will either be multiple sequences created from multiple integration times, or a combined sequence that takes the most appropriate data based upon the scene. In addition, the user can choose to vary the number of frames per integration time, as well as have the option to utilize an internal filter mechanism for attenuation or spectral data.

Certain applications require very wide thermal dynamic ranges, which may not be possible with a single integration time. The high speed infrared camera's dynamic range expansion mode will allow the user to cycle through exposure times at the fastest rate possible for the camera.

3.4 Event Triggering

In order to capture high speed events, infrared cameras must be properly synchronized. In the tire-testing example in Section 3.1 above, it is possible to have an optical encoder on the rotating tire that allows precise position location. The TTL signal generated by the optical encoder can be fed into the infrared camera to trigger the start of the recording sequence for the camera. The result is that every time the encoder sends the pulse, the camera exposes the infrared detector for a certain exposure time creating an image. This allows a real-time stop image sequence to be created via software.

In addition to the ability to accept an external TTL trigger, infrared cameras have other capabilities that improve their ability to capture high speed events. For example, certain trigger features permit the infrared camera to synchronize the trigger with the desired image capture. Because digital image frames are captured in real time, a pre-trigger permits the software to identify the beginning of a desired sequence that actually occurs before the trigger signal! Post-trigger delays are also available for aligning the frame capture with an event that follows the trigger after a programmable delay.

In addition, most high speed thermal cameras today have the ability to provide a trigger output to allow external devices to be synchronized with the thermal camera. Therefore the camera can slave or be slaved. Having both a trigger input and output is useful in an application that involves using multiple cameras to view the same target from different angles. In this case, the data can be assembled - via software - into a 3-dimensional rendering of the thermal profile.

3.5 Calibration: non-uniformity correction and radiometry

One of the challenges in obtaining the best data from a high performance infrared camera system was in maintaining a proper calibration. Calibration often refers to two different operations. One, non-uniformity correction, is necessary to calibrate the sensor for optimal image quality. The other calibration has to do with determining the temperature of objects based on their image brightness.

Non-uniformity correction is required to assure that the infrared detector array delivers the best possible image quality. Each pixel in the detector array inevitably has a slightly different gain and offset value. In addition, some pixels may have other anomalous properties that deviate from the norm. The gain and offset for all the pixels in the array need to be adjusted so that each pixel performs identically to the others. Variations can occur for a variety of reasons, including detector non-uniformity and optical affects such as the lens illumination non-uniformity that attenuates the apparent radiance near the edge of the image. Anomalous pixel signals must be replaced with nearest neighbor averages as is appropriate for the application.

To correct for the gain and offset, a calibration called Non Uniformity Correction (NUC) must be created. The process typically requires that the user expose the detector to a "cold" and "hot" blackbody source. An algorithm then corrects the detector signal non-uniformity. A similar process called Bad Pixel Replacement (BPR) is required for any pixels that are considered "bad" which means they deviate from certain thresholds set for evaluating uniformity or due to noisy behavior.

Non-uniformity correction is complicated because there are variations in pixel performance for each integration time. Therefore, this process would need to be performed for every integration time that the user selects. As high performance cameras can operate from 1us to >10ms, this means that in theory 10,000 calibrations need to be made. However, because of the linear response of the detector, recent advances have been possible to make this process transparent to the user. A process called TrueThermal allows the user to select any integration time and the camera will automatically reference a look up table of both NUC and BPR properties that were established either at the factory or at the user's site. In this situation, once a user selects the appropriate integration time, the camera system applies a predefined NUC and BPR table to allow instant and seamless operation.

Once the sensor is calibrated for uniform image quality, the camera can be calibrated for radiometry, or temperature measurement. If an infrared camera is properly calibrated, the object temperature can be determined based on the radiance signal in the thermal images, the background ambient temperature, possible atmospheric effects and the objects emissive properties. It is often particularly useful to be able to use the infrared camera to measure the temperature of objects (such as projectiles) traveling at high speeds. This finds applicability in several important situations, including: tracking of missiles, spacecraft and other objects, in determining the trajectory of bullets and projectiles and automatically identifying their origin based on trajectory information, and in creating thermal signatures for military targets.

Some users require that the thermal data be calibrated for radiometry. Again, this radiometric data will be dependent upon a specific integration time and must include the NUC and BPR corrections. In the past, for each integration time, a unique radiometric calibration would be required. Today, the TrueThermal calibration function facilitates the process, not only correcting for NUC and BPR, but also applying the appropriate radiometric calibration table to the data. This now allows the user to, in real time, change integration times and have fully corrected data for NUC, BPR and radiometric calibration.

4. Infrared Camera Applications

IR Inspection in Design, Test and Manufacturing:

Thermal imaging has become an extremely valuable technology in many industries as a tool to inspect and test different designs and processes. The thermal signatures can be a result of electrical, electro-mechanical, chemical or other causes. Thermal images reveal heat dissipation, thermal conductance, non-uniformities as well as other important diagnostic factors.

Hyperspectral and Gas Imaging, Remote Sensing:

Broadband infrared cameras are very useful for hyperspectral imaging (which involves the accumulation of a spectral set of times), gas imaging (which occurs at a sometimes very narrow portion of the infrared spectrum) and remote sensing (imaging the backscatter, reflection and emission differences of various materials). Powerful image processing software is available to facilitate the analysis of the resulting infrared images.

Target Signature Measurement and Tracking:

The spectral characteristics of vehicles, weapons and countermeasures have been found to be important for many applications. Broad spectral range, high resolution and high sensitivity are key features of infrared cameras for these applications. We offer multi-spectral imaging systems with a wide range of optics. In addition, we offer powerful data acquisition systems featuring real-time image capture and radiometric analysis.

Research and Development:

Thermal imaging is used extensively in engineering and scientific research centers around the world. Thermal imaging provides insight into critical information about an object's thermal and spectral characteristics. In certain circumstances, information can be obtained on high-speed events (available with high frame-rate cameras) as well as circumstances requiring large dynamic range (available with variable integration cameras). Key to the use of these imagers is often application-specific software that permits the detailed analysis of both two-dimensional images as well as arrays of image sequences.

Medical Imaging, Body Temperature Detection:

Many physiological conditions produce variations in body temperature and temperature distribution across the human body. As an example, the installation of thermographic cameras at airports has become a key Swine Flu and SARS screening tool for many areas around the world. Thermography has also been used as a screening tool for applications such as breast cancer and pain management.

Non-Destructive Test (NDT):

Thermal imaging is a non-invasive technique which when applied with specific stimulus provides a view into subsurface defects in difficult test samples. Inspection of composite aircraft parts is gaining wide acceptance in airframe manufacture and service. Advanced materials are finding their way into automotive and consumer products and thermographic NDT is a fast and wide area screening technique that is very cost effective.

Summary

Because of the impressive performance of MCT detector technology, high performance infrared cameras have become available that enable a wide variety of demanding thermal imaging applications. A selection of infrared cameras are available having mid-format to large-format detectors and with spectral sensitivity ranging in the short, mid and long-wave spectral bands. The cameras owe their versatility to certain features that include: high frame rate imaging, adjustable exposure time, event triggering enabling the capture of temporal thermal events, dynamic range expansion, non-uniformity correction and radiometric calibration. These performance capabilities and camera features enable a wide range of thermal imaging applications that were previously not possible, including: IR Inspection in design, test and manufacturing, hyperspectral imaging, gas detection, remote sensing, target signature measurement and tracking, R&D, medical imaging and NDT.

For a comprehensive copy of this article, please visit:
www.electrophysics.com/ezinehsirtherm
For more infrared cameras White Papers visit our online Knowledge Center:
www.electrophysics.com/infrared-cameras
Electrophysics Scientific Imaging
373 Route 46, Fairfield, NJ 07004
Phone: 973-882-0211 Fax: 973-882-0997

Article Source: http://EzineArticles.com/?expert=Josh_L._White

Article Source: http://EzineArticles.com/4849418

Increasing Website Traffic Through Google Images

Optimizing images is very important when optimizing any website or blog. If images are optimized correctly, they can bring a huge amount of traffic to your site. Image optimization is highly advantageous but the most underused when it comes to optimizing websites to increase rankings and traffic.

Depending on niche and images used, one may be able to attract a great deal of extra visitors easily with very little additional work. Following are a few points you can put into practice when optimizing your website:

1. Insert Keywords in your Alt text

This step is the most useful and important when optimizing images. Select a keyword or phrase which is relevant and popular to describe your image and web page. This alt text should be inserted in the code for your image file.

For example:

Here are a few more specific rules:

If the image is just decorated text, put the text in the alt attribute 

If the image is used to create horizontal lines, bullets in a list or other similar decoration, it is fine to have an empty alt attribute (alt= "") 

If the image represents a lot of important information, try to summarize it in a short line and ass a longdesc link to a more detailed description.

2. Optimize the page with the image 

Optimizing the actual page for search engines improves graphic images search. Search engines also look at text surrounding a graphic image to determine relevancy. It is recommended that descriptive text with your targeted keywords be placed immediately before or after the image itself. Also text within the anchor tag and next to the anchor text is especially going to influence image-search rankings. If you do a search for any term on Google Image, you'll find a short description of around 20 characters below every image; the keyword is listed in bold as well.

3. Name images with Descriptive Titles 

If you have an image of Bill Clinton, you could use the term "bill-clinton.jpg" to name your image file, instead of just using the original file name which could be something like "c789.jpg". You can name the images exactly the same way as my alt text.

4. Determine overall content relevance using AdSense 

This method can be used specifically used for Google Image Search. It is not very important to follow this but it is very useful to determine the relevance of your content with respect to your image. It will tell you how Google thinks about the overall theme of what your page is about. Keep changing your content until the AdSense unit on the page reflects the keywords you want to target. This method does not only apply to Google images but it is a generally a helpful method and it improves your overall latent semantic indexing. Your site will appear more relevant to Google for targeted keywords and phrases.

5. Use Social Site Tags for your images 

If you are using images with little or no textual content, it will be useful to tag your images using internal tagging or social tags like Technorati. This may add more weight to your image and help it rank better. And if you are uploading your images using Flickr, remember to use appropriate keywords as well.

6. Make your image file accessible to search engines 

Check that your robots.txt file does not restrict search engines from accessing your image files. Try not to use javascript links on image files as it will limit search engine access as well.

7. Hotlink Images from Google Search Results 

Type a search query for the image you want. Then visit the original web page and copy the image location to your own website (hotlink it). Your website might show up high among image search results. Most of the images in the top row are actually hotlinked and rank better than the original image source. Well this method is frowned upon by most webmasters because it violates copyrights issues.

8. Use Images about 'Hot topics' 

Deliberately use images to catch visitors who are searching for hot topics or trending topics. Through Google Trends you can find this out. Make sure your content is relevant to the image used for more impact.

9. Add an optimized web page on your website and link the image to that page. 

Users can access this page via the 'back' anchor on the new page when they find your page through Google Image Search.

10. Monitor the Number of Indexed Google Images 

An important aspect of Google Image Search optimization is to monitor how many images on your website are indexed by Google if you have taken the right steps to optimize your image. Just type site: vinfotech.com and check the images indexed for vinfotech. Instead of vinfotech.com, just type in your website to get indexed images.

The author helps clients in achieving the full potential of their websites and in generating traffic through reliable, ethical methods. The author works at Web Design Company Ocular Concepts and looks after Drupal Website Design

Article Source: http://EzineArticles.com/?expert=Adam_Ada

Article Source: http://EzineArticles.com/3880823

Boost Traffic to Your Website by Optimizing Images

In terms of aesthetics, images are an integral part of website design. They provide site visitors instant visual stimulation. In terms of SEO, images can be optimized and bring additional visitors to a website.

But images are often overlooked in SEO. But if we see next to regular search on a search engine Image Search is the fastest growing vertical search in the space. Compared to shopping, news, blogging, etc., image search has them beat by a mile. However, what's even more important about image search, is how the search engines are utilizing and incorporating them into their regular search results.

Nowadays images are incorporated in a lot of different ways. You'll see images coming up with the news one boxes, with descriptions of videos, a group of images could appear at the bottom of a page, as opposed to the top of the page. All of the search engines are striving to make the results more relevant and incorporating images into the results is definitely part of that strategy.

Here are few tips to optimize your site's images for the search engines.

o Names of the images: 

Avoid using any needless, uninformative words such as 'and', 'thus', 'or' and so on because they makes your content longer and complicated and make the reader lose interest. Make file names as clear and short as possible. The image name will appear beneath the graphic image in search results. Make the image names of your files match what is actually represented in the file Do NOT expect your photo editing program's default settings to give you optimized file names Default names communicate nothing to the search engines on their own. Make sure to set up your own file naming structure in advance. Use dashes between the words of images, rather than underscores. Nobody likes detailed data. Try to think of keywords that usually grab your attention and frame the file names.

o Use Alt attribute of the img tag: 

Search Engines only know what you tell them. Therefore, if we want a search engine to understand that a graphic is an ad, decorated text or coupon for your services you have to tell it. We do this via ALT (alternative) tags. ALT tags should contain a description of what the image is. It is a labeling device to translate your image into text for search engines. It also translates your image into a textual reference for users with visual handicaps. Finally, if a user has images turned off or a slow connection, they are presented with your textual alternative so your page remains relevantly contextual.

Search engine also gives importance to alt tag to determine the page rank of the website. Google indexes the text given in the ALT tags of images. The ALT attribute is also shown when the user pass over the image with his mouse. 

Things to keep in mind while preparing alt tags for images:

1. Alt text is the best description of the image. 

2. It should be short and simple. Avoid giving unnecessary details using alt tag. 

3. If your image is decorative text then just use the same text in alt text. 

4. If the image is the bullets we can leave the alt text blank. 

5. Use two or three keywords at the most while optimizing images with alt text. Don't use so many keywords.

Alt tag is a useful source to serve the problem of many web browsers displaying the image differently, and some browsers even don't support some types of images in such cases alt tag is very useful.

o Robots.txt file: 

Ensure that the folder you are storing your images in is not blocked by your robots.txt file. Store your navigational and "structural" type graphics in one folder, and block that from the spiders, store the pictures of products, events, or news related images in another folder and open that one to the spiders.

o Image freshness 

Keep images fresh. If you're targeting high popularity keywords it's worth experimenting with re-uploading images. Image freshness is a contextual clue for the search engines and could affect relevancy. Re-uploading your images to keep them fresh.

o Reasonable image file size 

The image size also plays an important role while loading the page. If the image is too big the page will take too long to get displayed, always specify height and width of the image so that the image will be loaded easily.

o Limited number of images per page 

Don't use too many images in a web page it makes your web page slow.

o Check images aren't being filtered out in Google Safe Search Filter

o Use a Caption for Your Image: 

Placing a small caption directly under, on top or on the side of your image will help queue the search engines what the image is about. With a caption, you can be a little more descriptive about the picture than with the alt attribute, but again, make it flow natural.

o Design unique images to differentiate yourself

o Include Images With Articles, & Press Releases: 

If you are sending out an article or a press release, don't forget to include an image, or a url to an image that the news outlets can utilized for their version of your news. By supplying the link to the image, it can encourage them to link to the image itself straight from your own website. Adding images to articles and press releases makes them more appealing to the reader.Boost internal linking and traffic by linking images to the relevant articles.

Shilpa Singh, Director Himshilp- Internet Marketing Consultants handling SEO, SEM. http://www.himshilp.com

Article Source: http://EzineArticles.com/?expert=Shilpa_Wilson_Singh

Article Source: http://EzineArticles.com/2701096

If You Care For Image - You Can't Care For Truth

Images have acquired extremely important role in the modern world. We know more people by their images rather than as an individual. People do everything to change their image, built their image and maintain a good image. If your image becomes outstanding, you tend to acquire the status of a "celebrity" who are like living Gods in the modern world. Therefore, images are everywhere in different shapes and forms. From the TV channels who displays thousands of images of so called celebrities like politicians, film stars, sports stars and even journalists. People have more trust in these celebrities than the people they know well like their parents, children or their spouses.

Most people can not distinguish image from reality. They take the image of the person as reality and build their personality from their own imagination. The personality woven around the image is so perfect that they fail to appreciate the real people whom they know. They find the real people imperfect while their ideal person lives only in their imagination.

When we know the complete personality of a human being, we may not like all facets of his or her personality. A real person is unpredictable. His mood changes every moment and he do not behave in the manner as we expect them to behave. Images are much better as they never change and never go against our expectation. So when we only have the image of the celebrity, the unpleasant aspects are hidden from our eyes and there we find a perfect person.

However, images are quite deceptive as they are only two dimensional and taken from only one angle. There is no way to know the complete person from an image as all other facets of the person lies completely hidden from the eyes. Despite our best attempt, we just can't see the full person whose image is before our eyes.

The real person is however, visible from all angles. We see the image of a person from thousands of angle and yet we recognize the person as we know that there is only one person behind all these images. Our minds have the capability to synthesize these images and form the real person with full personality in our mind.

As God has been just, he has not made any man either full of virtues or full or evil. In fact the good and evil are put together in every person in almost same proportions. Hence one who knows a person often get disappointed as even a genius person is not free from defects and on the average, he may not be better than any other person.

Image Consciousness

It is not unusual to notice that all celebrities would like to be photographed only in a certain pose because they know that they are photogenic only from few angles. They would also like to be photographed with only certain outfits because they know that they looked best with those outfits and people want them only in such outfits.

These outfits may vary. While some people may like to display their branded cloths as a mark of their riches, others like Gandhi may hardly wear any cloth in order to identify him with poor. Imagine a celebrity like Britney spears dressed up in Indian Sari or Mahatma Gandhi being dressed up in designer's suit.

People are so used to images that they often create the image of God based on their own imagination. For example, Indian Gods like Krishna, Rama or Vishnu are all dressed up like a King with golden and diamond jewels and armed with deadly weapons while Shiva, the God of destruction, is always dressed like ascetic with serpent around his neck. On the contrary Jesus is dressed like a saint whose appears to be ready to give sermons. Buddha is always found sitting in meditation. Little does people realize that none has ever seen God, yet the Gods who have multi-facet personalities are molded into an image covering the real persons they are and hence concealing the truth from the eyes of the beholder.

These images have become so important to most people over the ages that they confuse these images of human imagination as God and never seek to know the reality which lies beyond all images. It is for this reason that all religions asked their followers to shun image worship and seeks to know the Reality. Lord says in Bible

"Of what value is an idol, since a man has carved it? Or an image that teaches lies? For he who makes it trusts in his own creation; he makes idols that cannot speak. Woe to him who says to wood, 'Come to life!' Or to lifeless stone, 'Wake up!' Can it give guidance? It is covered with gold and silver; there is no breath in it. (Habakkuk 2: 18-19)

While image are a convenient method to identify a person yet it is most disastrous to confuse image with reality. Images can be a means to an end but not an end in itself. One has to use the image to reach the truth but break the image as soon as the reality becomes visible. Thereafter the focus must be to the reality and not on the image.

The Trap of Image

Most of us without our conscious knowledge are actually trapped in the images just like most film stars gradually develop an image of themselves and then they end up doing similar roles in all their lifetime. Their fans become so used to their image that they do not want their heroes to play any role contrary to their image. The stars who develop their image in order to become celebrity soon find themselves trapped in their own images like a man trapped inside a prison walls.

Even ordinary people can not avoid the trap of their own images. Some people develop the image of being good and nice. They become so serious about their own images that they can not do any bad thing to others even if they wish to do. They may hate a person yet they would avoid being critical to him as their image would get destroyed by such acts.

Similarly, people are trapped in the image of father, mother, leader, businessman, son, daughter, nice, effective and ruthless and so on. Even an evil person, often become so trapped in his own image that he fears that if he becomes nice and kind to even one person, his image would be destroyed and people would stop fearing him. His fear is not very different to a nice person who avoids being critical for the fear of losing love of the people.

Truth is beyond all Images

The only method to be truthful is to break all images. The images of self are as much an illusion as the image of God. Some people consider God as only kind and loving. The reality is that God is extremely unkind to people who breaks his law and punishes the people who does evil acts. Everyday, we see such evil people getting punished yet we fail to accept this truth that God does not always love and kind. This truth has been stated in every religion (Thou shall reap what you sow), yet people ignore this aspect of God so that they can keep on breaking all His rules and still hope His love and generosity.

In the same way people often portrays God as "Just" who like a Justice of Court weights the good and bad deeds (Karma) of every person and awards or punishes strictly based on his karma. This again is only part truth as God is also kind who forgives the people who repents and apologizes. God also listen to the prayers of the man that comes from his heart and allow everyone to reform himself. This aspect of God is also stated in every scripture, yet some people take Karma as the inviolable rule.

This two aspect of God may look contradictory, if we treat God as Image which can have only one dimension. However, if we consider God as a living Reality, we know that these two nature are part of every person's personality. We all balance justice with kindness for all people whom we love. Since man is part of God and created in the image of God, the nature of God can not be any different.

Thus the Reality known as God can never be trapped in any form of image. One can know God only through intuition as God is a multidimensional Reality and not single dimension image. Only when the man is willing to break the image of God as created by the world, he would be able to know God in His full majesty.

Truth Consciousness

The seeker of truth has to therefore, demolish all images of the self and the world so that truth can manifest itself to the person. This can be a difficult task in the beginning but become much easier once the journey for truth is undertaken. If the attempt of the person is know the real person, he can never hope to rely on the image as such knowledge is impossible without interacting with the real person and drawing his own inferences based on the experience. Therefore, get ready to break all images if you desire to know the truth which alone is eternal and real.

A Brief Profile of Dr Awdhesh K Singh

I am an Engineer by education , a public officer by profession and a spiritual person by intuition.

I hold my PhD degree in the field of E-Governance.

I am a founding member of The Aatmic Science Foundation (The Science of Soul Foundation) that is working for the synthesis between all religions, spirituality and sciences.

The website of the foundation is http://www.scienceofsoul.com

My main area of study and research is to use religions, spirituality and scientific methods of investigations to understand and solve the real life problems of human beings.

I have published hundreds of articles and research papers on this topic on various websites and journals.

Please contact me on my email aksinghirs [a] yahoo.com for any help, suggestions or feedback.

Article Source: http://EzineArticles.com/?expert=Dr_Awdhesh_Singh

Article Source: http://EzineArticles.com/2374389

Photography - Understanding Digital Image Formats

Images produced by digital cameras now rival the quality of our finest photographic film stocks. But the nature of a digital image shares almost nothing in common with the analog image captured in a film emulsion.

An image captured in film is an incredibly complex physical object that has a life of its own, and can be interpreted directly by inspection with the human eye. A digital image, on the other hand, is an electronic representation of a scene - a sequence of numbers specifying red, green, and blue light intensities that requires some form of software to render it into a visual form that can be displayed on a suitable imaging device, like a photo-printer.

When an image is captured digitally, it is done with a mosaic of light-sensitive electronic pixels. These pixels are actually independent square-shaped photodiodes which are arranged in the form of a large tiled surface. Well, large from the point of view of a single pixel, since if we were to enlarge the pixel to the size of a kitchen floor tile, then the area covered by the entire image sensor would be about the same as that of a football stadium.

A typical medium-resolution digital camera might have about 4000 electronic pixels arrayed along one edge of its image sensor, and about 2500 along the other, making for around 10 million pixels overall. The image sensor in this case would be said to have a 10 megapixel resolution.

Now, when an image is recorded electronically, what each pixel on the sensor measures is the amount of energy the light imparts to it during the photographic exposure. Or in simpler terms, the brightness of the light. This large array of numbers is known as the RAW format of the image. It is, in effect, the digital equivalent of the film negative (or positive in the case of slide film), since it carries ALL the information associated with the exposure.

As it happens, you cannot simply interpret these RAW image records in a color-by-the-numbers type fashion. If you were to assign the color and brightness of each pixel to a corresponding printed pixel on a piece of photographic paper, or on a computer screen, you would not see a pleasing representation of the scene that was photographed.

The reason for this is that the way our eyes respond to color brightness is different than the way electronic pixels respond to it. Our eyes are less responsive to large changes in brightness than are electronic pixels. The RAW numbers need to be processed in a way that compensates for this difference.

What this means is that a lot of number crunching needs to be performed to get the best result from our RAW image before it is printed in any form. This might be done inside the camera if you want to immediately see a preview of the result on your camera's LCD screen. Or it might be done using complex image processing software on your PC, once you have downloaded the image. Until then, the RAW image needs to be stored for later use.

Unfortunately, in the race to conquer the digital photography landscape, digital camera manufacturers adopted a first-to-build is first-to-dominate philosophy and created their own proprietary versions of the RAW image format. A Canon RAW image, therefore, is formatted differently than a Nikon RAW image for the exact same image. Due to the proliferation of RAW formats, image processing software now has to cope with hundreds of competing RAW image formats. In practice this is just not possible, so your imaging processing software (if it comes from a vendor other than your camera manufacturer) is likely to support only the major RAW formats, like for example Nikon's NEF format, Canon's CR2 format, and Fuji's RAF format.

This situation is likely to improve in time, however. Adobe has entered the digital imaging fray by publishing an open standard for a RAW image format that it calls Digital Negative, or DNG. Slowly, camera manufacturers, like Hasselblad, Leica, Ricoh, and Samsung are building DNG support into their cameras, and with luck the larger players in the field will follow suit.

What this means, assuming that a standard such as DNG is adopted, is that when a photographer captures an image, stores it in RAW format, and then forgets about it for 10 years, they won't discover, when they get around to retrieving it again, that their image format has been obsoleted and there is no longer any software that can render the file into a viewable and printable image. For large corporations with millions of archived images to preserve, this kind of problem represents a logistic nightmare, and it is very costly to stay on top it.

In the long run, a standardized RAW format will ensure archival integrity of images, reduce headaches for unwary photographers the world over, and save them both time and money. DNG support is currently available in Adobe software packages such as Photoshop, and Photoshop Elements, and will likely migrate to third party image software packages as the standard is embraced. Adobe also offers a free Digital Negative Converter from its site which allows forward-thinking photographers to convert their existing RAW image format files into a DNG version as well.

As has been mentioned, software is needed to convert a RAW format image into one that can be displayed and printed. This is analogous to the "development" process for negative film. The most common image display format is JPEG (which stands for Joint Photographic Experts Group). The JPEG format is one that can support a great deal of compression, so that the final viewable image is substantially smaller in size (number of bytes) than the RAW image file. This means it can be sent on to others easily, via email for example. The JPEG format is also an industry standard image format, so the file can be opened and read by all commercial image processing software and a large number of open source image software packages.

Another standard image format is TIFF. However, TIFF file sizes are generally much larger than those for the equivalent JPEG image, so they are used mostly by professionals who need to produce large print reproductions with high resolution. In fact, the DNG standard is based on a version of TIFF.

Various image processing algorithms are applied to RAW images to convert them into printable form. This includes performing white balancing, which is the means by which an unwanted overall color cast is removed from the image. When a color cast is present, a photographed all-white object will render with an off-white component that subtracts from image fidelity. The RAW image stored by your digital camera will likely have a record of the white balancing correction used when the image was created, but you are free to adjust this when editing the image derived from the RAW format.

It is important to appreciate that when you are trying to the create the best possible printable image, you need to start with the original RAW image file. Once a printable version has been created, such as a JPEG version, the applied image processing algorithms have "tossed out" a great deal of image information that was deemed unnecessary. These lossy operations are irreversible, and they limit your remaining options for tinkering with the image should you decide that the result is not quite what you are after. The solution is to return to the RAW format file and start over.

Because the differences in file sizes are so great, if you are not concerned with collecting RAW image files and processing them for the perfect image at a later date, you should consider allowing your camera to create JPEG images as the default, and ignore the RAW format altogether. This will improve the responsiveness of your camera, because you do not have to store the large RAW images to your memory card. If, for example, you are photographing a sports event, your frame-rate when shooting in the continuous mode will be greatly improved. Also, you will be able to record a much higher number of images to your memory card before it fills up.

On the other hand, if you will be photographing something of importance, do consider the implications of not using the RAW format to record your images. You might regret it later.

To help you select a suitable digital camera to get started with, I have put together an article for you about how to find the right Beginner Digital Camera

Whether you need a simple point-and-shoot model, or a more complex digital SLR model, you will find the answers, and greatly discounted digital camera offers, at http://www.bestdigitalcameradiscounts.com/

Article Source: http://EzineArticles.com/?expert=Stephen_J_Carter

Article Source: http://EzineArticles.com/1426988

How To Prepare Images And Photographs For The Web

The images you choose to use on your site are extremely important as they will say a lot about you as a business. Make sure that you choose images that are both eye-catching and of decent quality.

The key to good web images is to keep them as small as possible. Remember - the bigger your images are, the longer they will take to load when someone looks at your website. Images are good to add visual interest to your site, but if you add too many it may start to look cluttered.

Image-editing software

There are many image-editing software packages available, and almost all of them will be sufficient for basic editing of images for your website.

Probably the most popular choice is Adobe Photoshop - now available in both the full professional version and a cut-down version (Photoshop Elements) for home users. There are also many free image-editing programs available on the web which have almost identical functions to Photoshop.

In this guide we will show you how to use both Photoshop and GIMP, which is a free program available for download from http://www.gimp.org/.

File types

For photographs, and graphics with gradients (smooth blends of colours), we recommend that you save your images as JPEG files - these files are compressed so they will be relatively small in size, whilst still retaining the smooth colours without distorting.

For images with flat solid colours, such as an icon or text graphic, you should save as GIF files - These are better for crisp or blocky graphics because they are smaller in file size than JPEGs, but will make photographs look grainy.

For more information on file types and resolution see Saving for web.

Cropping

Sometimes you will need to 'trim' an image down to focus on a particular subject or remove unwanted detail around the edges of a photograph. Most imaging software will have tools for you to do this.

In Photoshop

1. Open the file you wish to edit by choosing 'Open...' in the File toolbar at the top of the window and selecting your image in the file browser.

2. Select the 'Crop' icon in the palette on the left, or press 'C' on your keyboard.

3. Click and drag from a point on the image to create a rectangle. - This is will be the section that you want to keep.

4. Don't worry if it's not right first time - you can resize the rectangle by clicking and dragging the corners before you are ready to crop.

5. To crop the image, double-click the rectangle you have made.

In GIMP

1. Open the file you wish to edit by choosing 'Open...' in the File toolbar at the top of the window and selecting your image in the file browser.

2. Select the scalpel icon ('Crop or Resize an image')in the palette on the left, or press 'shift + C' on your keyboard.

3. Click and drag from a point on the image to create a rectangle. - This is will be the section that you want to keep.

4. Don't worry if it's not right first time - you can resize the rectangle by clicking and dragging the corners before you are ready to crop, or specifying the width and height in the 'Crop & Resize' box.

5. To crop the image, double-click the rectangle you have made.

Cropping to size

Sometimes you will need to change the proportions of your image. In order to prevent your image stretching when you change either the width or height, you will need to crop it to size instead of resizing an image (that is already in proportion) - shown below.

For example, you have an image that is 250px high and 300px wide. You need the image to be square to use as a thumbnail for your website, so you'll need to lose that extra 50px from the width.

In Photoshop

1. Select the 'Crop' tool from the tool palette on the left or press 'C' on your keyboard.

2. Before using the crop tool on the image, type the required proportions of your new image in the options bar across the top of your window. e.g. width: 250px, height: 250px. Make sure you write 'px' for pixels after the number so that Photoshop doesn't think you're talking about centimetres.

3. Click and drag the crop tool on the image as you would normally. You will notice that the box has set proportions so you cannot change the shape of your rectangle as you drag - only the size.

4. Double-click the rectangle you have made to crop the image. As long as you set the proportions correctly beforehand, your image will be cropped and resized to the dimensions you need so you can save from here without further resizing.

In GIMP

1. Select the scalpel icon ('Crop or Resize an image')in the palette on the left, or press 'shift + C' on your keyboard.

2. Click (but don't drag) a point on the image to create your crop area

3. A 'crop and resize' pop-up window will appear where you can enter your required proportions in the 'width' and 'height' boxes. Make sure 'px' is selected so The GIMP knows you want to measure size in pixels.

4. When you change the width and height you will see the cropping area on your image change dimensions too. To change the position of this area within the image, change the values for 'Origin X' and 'Origin Y' fields in the crop & resize window.

5. When you're happy with the size and position, click 'Crop' or double-click the rectangle you have made to crop the image.

Resizing

The standard resolution for printed images is 300 dots per inch (dpi) and above, whereas for web images it is just 72 dpi. When you resize your images for web, you should always set the image resolution to 72 dpi, so you can see how big it will really look on screen before you put it on your website.

If you already have images on your website, you can find out how big they are by right-clicking on the image and selecting 'properties'. This will tell you the height and width of the image so you will know what size to make them in the future.

In Photoshop

1. Open the file you wish to edit by choosing 'Open...' in the File toolbar at the top of the window and selecting your image in the file browser.

2. Go to Image > Image Size... to see the current dimensions of the image.

3. To resize your image, change either the width or the height in pixels. If 'constrain proportions' is enabled (at the bottom) the image will resize both width and height at the same time. It is a good idea to keep this on so that your images will not stretch. See Cropping to size if you need to change the proportions of your image without stretching.

4. Make sure the resolution is set to 72 pixels/inch so you know you are seeing your image at its actual size.

5. Click OK to resize your image.

In GIMP

6. Open the file you wish to edit by choosing 'Open...' in the File toolbar at the top of the window and selecting your image in the file browser.

7. Go to Image > Scale Image... to see the current dimensions of the image.

8. To resize your image, change either the width or the height in pixels. The linked chain symbol means that if you change one dimension, the other will change as well. It is a good idea to keep this on so that your images will not stretch. See Cropping to size if you need to change the proportions of your image without stretching.

9. Make sure both the X and Y resolution is set to 72 pixels/inch so you know you are seeing your image at its actual size.

10. Click 'Scale' to resize your image.

Note: It is never a good idea make an image larger than it was before. Your image-editing software is forced to 'guess' details in the image and add new pixels, which often results in a blocky or blurry-looking image. This is known as pixellation. Making an image smaller on the other hand, is usually fine.

For this reason, it is good practice to keep your original large file saved in case you need to resize it again.

Saving for web

Remember - the larger your image is, the longer it will take to load. For people with a slower internet connection, a large image can take several minutes to appear.

Image size is not just about how many pixels you have. It is also dependent on the quality of the image, and how many different colours it is made from.

When you save images for use on the web, you will always have to sacrifice a certain amount of image quality in order for it to load in the quickest amount of time.

In Photoshop

1. Once you have finished editing your image, go to File > Save for web...

2. You will see a preview of how your image will look once it is saved.

3. Choose your file type from the first drop-down box on the right-hand side of the screen. For more information on choosing a file type for your image see 'File Types'.

4. Choose the quality of your saved image by moving the quality slider* left or right. You can also choose a quality setting from the drop-down menu below the file type (e.g. low, high, maximum etc.). Try to choose the lowest possible quality without affecting the image you see in the preview. If it looks blurry or gritty, you've gone too far.

5. Click 'save' and choose a file name for your image. (save it under a new name so you can keep a copy of your original image)

*Note: When saving a gif, instead of a 'quality' slider you will get a drop-down box where you can choose the amount of colours in your image. The fewer colours you have, the smaller your image will be. In many cases, your gifs may actually look better with fewer colours as it will be more consistent.

In GIMP

1. Once you have finished editing, go to File > Save As... (save it under a new name so you can keep a copy of your original image)

2. Click on "Select File Type" and select whichever one you need. For more information on choosing a file type for your image see 'File Types'.

3. Click 'save'

4. Choose the quality of your saved image by moving the quality slider* left or right. Try to choose the lowest possible quality without affecting the image you see in the preview. If it looks blurry or gritty, you've gone too far. (To see a preview of your saved file, just click 'Show Preview in image window'.

5. Click 'OK' to save your image.

*Note: When saving a gif, you will be asked whether to convert to indexed colour or grayscale. This will depend on whether or not your image has colour. Click 'export' and continue. The GIMP does not give you an option to specify colours or quality of your gif, so skip step 5 and save as normal.

John Brunsdon is a director of UK Web Design and Marketing company Tickbox Marketing (http://www.tickboxmarketing.co.uk). Before setting up Tickbox, John worked for the BBC News website for seven years and is a former national newspaper journalist.

http://www.tickboxmarketing.co.uk

Article Source: http://EzineArticles.com/?expert=John_Brunsdon

Article Source: http://EzineArticles.com/716448