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Image Compression and Various File Formats

One does not have to search the vast expanse just to realize the way digital images have conquered the visual scene. A lot of the graphics that flood the surrounding are products of sophisticated software that came in the advent of more advanced technology. These days, the computer has been the most reliable tool for generating flawless graphics of varying file sizes depending on the purposes it is created to serve its end user.

Times have changed indeed. More and more people are beginning to trade the conventional way of developing photographs since digital photos offers a wider range of options to cater even to the most discriminating of tastes. Nowadays there are many ways of optimizing the guise and usefulness of web site images.

Even though electronic advertising liberates a person from the expenses and restrictions of color duplication in print, it is still necessary to do a number of clever computation and negotiations to be able to achieve optimized images and pictures for several display monitors as well as modern access speeds available in today’s information superhighway (Red Tower Tech. org, 2008). The basic notion behind compressing graphics is to be able to reduce the image content’s byte size without sacrificing its attribute up to such intolerable degree.

The decrease in the amount of space consumed by the file permits the archive of additional graphics in a particular memory or disk. Furthermore, it lessens the amount of time needed for the transmission of certain graphics over the information superhighway as well as the time it takes for its complete download from a particular website (Tech Target, 2001). Getting some knowledge of which among the various graphic types can be best utilized guarantees that digitally captured pictures may be exploited at the utmost.

On one hand, other graphic types are great for achieving the best possible mixture of quality and space consumption when archiving pictures. On the other hand, some graphic types permit a simple retrieval from a poorly captured picture. Numerous graphic file formats are now in existence and innovations are not coming to an end so soon (Cambridge in Color, 2008). The idea of compression is a significant factor that differentiates various graphic formats. Documents that have undergone compression are considerably smaller than the ones that are not.

Such idea is divided into two categories namely lossless compression and lossy compression (Cambridge in Color, 2008). In the first type of compression scheme, a full range of graphic information is guaranteed to be kept. Consequently, documents consume a significant amount of space. Unlike in a lossless compression, the amount of space consumed by certain files is considerably smaller. However, some graphic information is gone as it has been carefully discarded in the process.

As a consequence, the compressed graphic is in no way a duplication of the original file. The noticeable variations found in the original file and the compressed graphics is referred to as the “compression artifacts” (Cambridge in Color, 2008). Image compression can be made possible in many available means. Among the various file formats, the GIF or the JPEG formats are generally employed for utilization in cyberspace (Tech Target, 2001). Images stored as a Graphic Interchange Format

The GIF file format, also known as the Graphic Interchange Format was introduced by the CompuServe Information Service in the year 1980 (Lynch & Horton, 2004). This type of file format promises to offer an effective way to disseminate graphics over the information superhighway. During the early part of the year 1990, the World Wide Web’s pioneer creators adopted this particular type of file format for its usefulness and popular recognition. The stunning profusion of graphics on cyberspace today is in this type of file format.

Moreover, nearly each and every web viewing software that does support images can present files in this type of format. Files in this type of format integrate a compression plot to limit the file capacity to the lowest. Such images are restricted to an eight – bit color range. Such color range has 256 or less colors in it. Certain insignificant modifications of the usual GIF graphic file format increase support for lucid hue and for the interlaced images in GIF format which was endorsed by the Netscape Navigator (Lynch & Horton, 2004).

This type of file format is usually employed for line craft and other graphics in which nonrepresentational figures are rather uncomplicated (Tech Target, 2001). The compression feature of the GIF formatted file It utilizes a rather simple method in compressing a file. Such method includes what is called the LZW which stands for Lempel Zev Welsch (Lynch & Horton, 2004). It extracts weaknesses in the computerized information without sacrificing such information or deforming the graphic. This method of image compression is advisable in working with graphics with sizable ranges of consistent hue.

It is not advisable to use this when dealing with image compression of complex images with many hues and elaborate textures (Lynch & Horton, 2004). Enhancing compression One may exploit the features of LZW’s scheme in image compression to enhance its performance thereby minimizing the capacity of the GIF formatted images. The idea is to decrease the amount of hues in a GIF formatted graphic to the least value required and to eliminate random hues that are unnecessary to display the figure.

A GIF formatted image cannot exceed a total number of 256 different hues. However, it can have minimal hues, as much as having just two, particularly, white and black. Graphics with lesser hues will compress more effectively when the LZW’s scheme of image compression is utilized (Lynch & Horton, 2004). Interlacing for the GIF formatted file The traditional GIF formatted image, which is also referred to as non – interlaced image loads a single thread of pixels step by step starting from the top until it reaches the bottom (Lynch & Horton, 2004).

From here, the display program presents each thread of the graphic as it slowly figures on screen. In the case of an interlaced GIF document, the graphics information is kept in a structure that permits the display program that assist interlaced GIFs to start to compose a representation in a lower resolution version of the full – sized GIF image that appear at the time the document is transferring the data from one computer system to the other.

A large number of the population recognize that the vague to well – defined animated result of interlacing visibly attractive, however, for the most part, the essential advantage of interlacing is that it provides the audience a sample of the complete scope of the image at the same time as it is being downloaded (Lynch & Horton, 2004). Interlacing is an excellent choice for bigger GIF formatted files in the likes of graphics and pictures (Lynch & Horton, 2004).

However, it not advisable to be used for tiny GIF formatted figures in the form of icons, navigation bars and buttons (Lynch & Horton, 2004). These tiny figures will fill the monitor more rapidly as a standard GIF formatted file, in which case, reserved as non – interlaced (Lynch & Horton, 2004). Normally, the amount of space consumed by GIF formatted files is not considerably affected by interlacing (Lynch & Horton, 2004). Transparency feature of the GIF formatted file

Formatting in GIF permits one to select hues from a search table for purposes of creating transparency in the graphics. Photoshops and other software of the same kind may be utilized to do some editions to the graphics as well as to pick hues from the palette to effect transparency (Lynch & Horton, 2004). In most cases, the selected hue will become the image background. Sadly, the transparency feature of GIF formatted graphics is no way refined. As a result, all pixels of the same hue will be affected by the transparency feature whenever utilized (Lynch & Horton, 2004).

Transparent GIF formatted images with antialiasing content generates unsatisfactory outcomes (Lynch & Horton, 2004). At an instant when Photoshops and other software of the same kind has been utilized to produce a shape situated in contrast to a particular background hue, such programs will affect smoothness by means of incorporating pixels of intermediary hues at the length of the borders around the shape. Such procedure which is also referred to the antialiasing technique enhances the appearance of the graphics on screen by toning down rough ends (Lynch & Horton, 2004).

Whenever the transparency feature is utilized for a background hue and after that the same graphic is applied for a web site situated next to a another background hue, difficulty starts to build up. Nonetheless, the graphic’s pixels that have been smoothened will match up to the initial hue of the background. Even while the transparency feature of the GIF formatted graphics performs well with complicated figures, it can still be counted on for regular visual images too (Lynch & Horton, 2004). The basics of animation as a GIF formatted file

Files saved as GIF permits the grouping of multiple graphics of the same file format in a particular file for the purposes of animation. But then again, such operation of the GIF has numerous disadvantages of its own. From one frame to the other, a GIF formatted file is not compressed. Citing for example, four graphics, each measuring 30KB will amount to a total of 120 kilobytes when combined (Lynch & Horton, 2004). This 120 kilobytes graphic in itself will be set in the wire in motion. To some extent, the load of the GIF formatted files is kept smaller.

This is because prior to having been completely downloaded, frames already fill the screen and graphics is shown as it flows towards the user. One more disadvantage of an animation created as GIF formatted files is the fact that it is an annoyance as well as a possible disturbance. The absence of interface commands for animations created as GIFs allows the file to be played beyond control. At the moment looping has been allowed, GIF formatted animation will continue to play repeatedly (Lynch & Horton, 2004).

Instances wherein animations created in the GIF file format are utilized significantly are quite unusual. Moreover, such animations normally sidetrack the attention of their audience away from the most important content of the web site. Whenever a GIF formatted animation is being utilized as a content, meaning used as a tool to demonstrate a particular context or method, in such cases where animations are of significant importance, it is advisable to do so in moderation (Lynch & Horton, 2004).

Graphic imaging utilizing the Joint Photographic Experts Group technique Another image compression method often utilized in the information superhighway to keep storage spaces at the bare minimum is the JPEG file format. JPEG as an image compression method stands for Joint Photographic Experts Group (Lynch & Horton, 2004). As compared to other images formatted as GIF, graphics in JPEG format consists of 24 bit (Lynch & Horton, 2004). Twenty – four bit images are complete hue graphics. They are also referred to as graphics in true color (Lynch & Horton, 2004).

Graphics in this file format have caused a great attention from various industries including photography, art, advertising, medicine and other respects where graphic quality is of crucial significance and to whom hue conformity is not possibly negotiated by an 8 bit hue dithered image. The latest version for the JPEG format is referred to as the “progressive Joint Photographic Expert Group” graphic (Lynch & Horton, 2004). It provides such files the similar slowly formed display viewed in files formatted as interlaced GIF (Lynch & Horton, 2004).

Similar to GIF formatted graphics that are interlaced, graphics saved as progressive JPEG files usually consumes longer download time than the conventional JPEG file. However, these files present to their audiences a faster sneak peak (Lynch & Horton, 2004). This particular image compression method utilizes a complicated numerical system referred to as the “discrete cosine transformation” to create a descending range of graphic compression (Lynch & Horton, 2004). The compression level to be administered to a particular JPEG formatted graphic may be selected.

However, the quality of the graphics must also be decided upon. Files in this particular format can reach unbelievable compression percentages as much as a 100% reduction from its initial size (Lynch & Horton, 2004). This can be achieved since the algorithm of this file format rejects what it perceives to be the insignificant information as it condenses the graphics. Such procedure is referred to as the “lossy” image compression method (Lynch & Horton, 2004). The moment the graphic has undergone compression, the information is gone and may not be retrieved from the graphic content.

It is important to constantly store the original graphic content that is still uncompressed to serve as a backup file for future references (Lynch & Horton, 2004). As the name implies, JPEG formatted files are intended for archiving pictorial representations. Additionally, JPEG files have developed into a regular format for saving digital pictures as well as presenting vivid images over the information superhighway. In comparison, JPEG formatted images are not quite different from their TIFF counterparts. Nonetheless, JPEG graphics has their downside to them too.

Such files utilize what is called a “lossy compression” method (Cambridge in Color, 2008). However, the advantage of choosing JPEG file compression method rests in the flexibility these files possess. Truly, this type of format is equipped with selections whose options may be modified to best suit the requirements of a particular graphic representation (Cambridge in Color, 2008). JPEG graphics reaches a lesser amount of space consumed by a file by means of image compression where significant details are stored and unimportant ones are rejected in the process.

This is made possible by manipulating the truth that the naked eye recognizes slight hue intensity variations than hue discrepancies. Thus the compression level attained is greatly reliant upon the graphic information. Graphics registering an elevated noise intensity or too much information may not be effortlessly compressed, as compared to graphics with even skies and slight grain may be easily compressed (Cambridge in Color, 2008). The algorithm of this particular file format has a four phased compression method. Initially, the algorithm slices up a graphic into divided blocks in a pixel size of 8×8 (PREPRESSURE.

com, 2008). Each block is calculated separately. This is the reason why when compression has been greatly applied on each block or sets of blocks for that matter, they become easily recognizable. The algorithm of this file format is founded on the distinction of the human perception when it comes to hue intensity or luminance and hue variation or chrominance (PREPRESSURE. com, 2008). The JPEG algorithm does not scrutinize the CMYK or RGB hue values rather the graphic information are initially translated into a hue intensity of hue variation gap in the likes of YUV (PREPRESSURE. com, 2008).

This permits individual compression for both aspects. Since hue intensity is more important than hue variation as far as the human senses are concerned, the algorithm maintains more of the hue intensity whenever graphics are compressed (PREPRESSURE. com, 2008). Subsequently, the application of the DCT which stands for the discrete cosine transform method for the complete range of blocks is performed (PREPRESSURE. com, 2008). It is a sophisticated method that breaks free every pixel. It substitutes the concrete hue information for every pixel for estimates that are comparative to the mean of the whole pattern that is being scrutinized.

At this point, there has been no compression that is taking place just yet. The estimates for every pixel is just been substituted by the “DCT coefficients” in a pattern of the same dimension as that of the pixels (PREPRESSURE. com, 2008). Afterwards, the real compression takes place. Initially, the quality of the graphics is viewed by the software that has been applied. And then, it computes charts of quantization factors, individually for the hue intensity and another for the hue variation. These charts are then utilized to determine the values of the coefficients in DCT.

Every value is divided by a specific variable from the quantization chart. The resulting value is rounded off. The product is that minor and insignificant values of the coefficient will be substituted by zero. The more significant coefficients will be precision deficit. Rounding off the final results brings about graphic quality deficit in the resulting images (PREPRESSURE. com, 2008). The consequential information is a record of smooth “DCT coefficients” (PREPRESSURE. com 2008). The final tread in the course is the compression of such coefficients using either the arithmetic of the Huffman encoding method (PREPRESSURE.

com, 2008). Generally, the latter is often employed. In this case, a lossless or secon compression is being utilized (PREPRESSURE. com, 2008). By means of placing more than one compression algorithms ahead of one and the other, a JPEG file format reaches significant compression percentages (PREPRESSURE. com, 2008). Furthermore, for prepress utilization, image compression up to a fifth of the original file size is simple (PREPRESSURE. com, 2008). More significantly, in the case of website publishing and electronic mail correspondence, a 20:1 ratio can be made possible (PREPRESSURE.

com, 2008). Decompression, as far as the JPEG file format is concerned is maintained in the second level of the PostScript as well as the 3 RIP’s (PREPRESSURE. com, 2008). The aforementioned is an implication that lighter files may be transmitted over the network toward an RIP which liberates the transfer post more rapidly, reduces operating cost on the print server and keeps the RIP at a swift (PREPRESSURE. com, 2008). Besides, it is useful to acquire an illustrative perception for the way differences in the compression levels can affect the quality of the graphic representation.

At a hundred percent, the distinction between a compressed graphics from its uncompressed counterpart can go unnoticed. The algorithm of this particular file format gives more importance to the sharp contrast ends over more fine consistencies. At the same time as the quality of compressed graphics declines, the algorithm is obliged to let go of the quality of some visually outstanding consistencies so as to go on minimizing the amount of space the graphics can consume (Cambridge in Color, 2008).

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