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Entropy and Gibbs distribution in image processing : an historical perspective

Battiato S.

Image Processing & Communications

2001

Vol. 7, no 3-4

35-50

This paper presents an historical overview about the entropy and its applications for the solution of inferential statistical problems in image processing. This survey covers some of the more important entropy-based research approaches. A brief introduction to the mathematical details and foundations about the basic concepts of Markov Random Fields (MRF} and related Gibbs sampling is also given. The information entropy is a mathematical measure of information or uncertainty derived from a probabilistic model. The paper starting from the seminal works of C. Shannon and of E.T. Javnes and of S. Geman and D. German discusses results obtained using different related techniques in image restoration, analysis and synthesis of textures and saliency maps construction. The paper moreover gives useful suggestions about the trend of development in future research

Watermarking for images based on color manipulation and block subdivision

Battiato S., Castorina A.

Image Processing & Communications

2000

Vol. 6, no 1-2

29-38

In this paper we present a new watermarking scheme for color images. The method represents an improvement and a loose variation of the work done in [l, 2], where the authors proposed to alter the colors of a given image in an imperceptible way. Despite the theoretical accuracy of the method, an intensive testing has shown the weakness against some common image processing techniques in particular: JPEG compression, scaling and low-pass filtering. Experimental results will be produced, in order to demonstrate the validity of our new approach.