Image Compression

  • David Salomon

Modern computers employ graphics extensively. Window-based operating systems display the disk’s file directory graphically. The progress of many system operations, such as downloading a file, may also be displayed graphically. Many applications provide a graphical user interface (GUI), which makes it easier to use the program and to interpret displayed results. Computer graphics is used in many areas in everyday life to convert many types of complex information to images. Images are thus important, but they tend to be big! Since modern hardware can display many colors, it is common to have a pixel represented internally as a 24-bit number, where the precentages of red, green and blue occupy 8 bits each. Such a 24-bit pixel can specify one of 224 ≈ 16.78 million colors. An image at a resolution of 512×512 that consists of such pixels thus occupies 786,432 bytes. At a resolution of 1024 × 1024 it gets four times as big, requiring 3,145,728 bytes. Movies are also commonly used with computers, making for even bigger images. This is why image compression is so important. An important feature of image compression is that it can be lossy. An image, after all, exists for people to look at, so, when it is compressed, it is okay to lose image features for which the human eye is not sensitive. This is one of the main ideas behind JPEG and other lossy image compression methods described in this chapter.


Discrete Cosine Transform Image Compression Data Unit Iterate Function System Discrete Cosine Transform Coefficient 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer Science+Business Media New York 1998

Authors and Affiliations

  • David Salomon
    • 1
  1. 1.Department of Computer ScienceCalifornia State UniversityNorthridgeUSA

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