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Chapter 2:
Source Models and Entropy
Any information-generating process can be viewed as a source that emits a sequence of symbols chosen from a finite alphabet. For example, this text has been generated by a source with an alphabet that contains all the ASCII symbols. Similarly, a computer performs its computations on binary data, and such data may be considered as a sequence of symbols generated by a source with a binary alphabet composed of 0 and 1. In the case of images, one may think of an n-bit image as being generated by a source with an alphabet of 2 n symbols representing the possible code values. The ordering of the sequence produced by an image source might correspond to adjacent pixel values based on a 1-D raster scan, or it might correspond to values taken from a 2-D block of pixels. It is advantageous to develop models for image sources in order to measure the “information” conveyed by these sequences of symbols. In the following chapters, we examine several source models and related information theory concepts that are useful in image compression.
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