Abstract

We present in this brief a new way to measure the information in a signal, based on noise modeling. We show that the use of such an entropy-related measure leads to good results for signal restoration. I. INTRODUCTION The term "entropy" is due to Clausius (1865), and the concept of entropy was introduced by Boltzmann into statistical mechanics, in order to measure the number of microscopic ways that a given macroscopic state can be realized. Shannon [11] founded the mathematical theory of communication when he suggested that the information gained in a measurement depends on the number of possible outcomes out of which one is realized. Shannon also suggested that the entropy can be used for maximization of the bits transferred under a quality constraint. Jaynes [7] proposed to use the entropy measure for radio interometric image deconvolution, in order to select in a set of possible solutions which contains the minimum of information, or following his entropy definition, that which h...

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