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Compression reduces the number of bits required to represent a signal. The appropriate compression strategy is a function of the type of signal to be compressed. Here, we focus on images, which can be single component (., gray scale) or multiple component (., three-component color or highercomponent remote sensing data). Each component can be considered to be an “image” — a two-dimensional (2D) array of pixels, and this chapter reviews the fundamentals of image compression as a 2D signal with specific statistical characteristics. . | Image Databases Search and Retrieval of Digital Imagery Edited by Vittorio Castelli Lawrence D. Bergman Copyright 2002 John Wiley Sons Inc. ISBNs 0-471-32116-8 Hardback 0-471-22463-4 Electronic 8 Image Compression A Review SHEILA S. HEMAMI Cornell University Ithaca New York INTRODUCTION Compression reduces the number of bits required to represent a signal. The appropriate compression strategy is a function of the type of signal to be compressed. Here we focus on images which can be single component . gray scale or multiple component . three-component color or higher-component remote sensing data . Each component can be considered to be an image a two-dimensional 2D array of pixels and this chapter reviews the fundamentals of image compression as a 2D signal with specific statistical characteristics. Application to multicomponent imagery is achieved by separately compressing each component. Compression of the higher-dimensional multicomponent data is possible it is very uncommon so we concentrate on 2D image compression. Compression can be thought of as redundancy reduction its goal is to eliminate the redundancy in the data to provide an efficient representation that preserves only the essential information. Compression can be performed in one of the two regimes lossless compression and lossy compression. Lossless compression permits an exact recovery of the original signal and permits compression ratios for images of not more than approximately 4 1. In lossy compression the original signal cannot be recovered from the compressed representation. Lossy compression can provide images that are visually equivalent to the original at compression ratios that range from 8 1 to 20 1 depending on the image content. Incorporation of human visual system characteristics can be important in providing high-quality lossy compression. Higher compression ratios are possible but they produce a visual difference between the original and the compressed images. A block .

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