Abstract

Shannon's definition of entropy is critically examined and a new definition of classical entropy based on the exponential behavior of information gain is proposed along with its justification. The concept is extended to defining the global, local, and conditional entropy of a gray-level image. Based on these definitions four algorithms for object extraction are developed. One of these algorithms uses a Poisson distribution-based model of an ideal image. A concept of positional entropy giving any information regarding the location of an object in a scene is introduced. >

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