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Spatial Mutual Information and PageRank-Based Contrast Enhancement and Quality-Aware Relative Contrast Measure

Abstract

This paper proposes a novel algorithm for global contrast enhancement using a new definition of spatial mutual information (SMI) of gray levels of an input image and PageRank algorithm. The gray levels are used to represent nodes in PageRank algorithm, and the weights between the nodes are computed according to their dependence and spatial spread over the image, which is quantified by using SMI. The rank vector of gray levels resulted from PageRank algorithm is used in mapping input gray levels to output. The damping factor of the PageRank algorithm is utilized to control the level of perceived global contrast on the output image. Furthermore, a new metric is proposed for image quality-aware relative contrast measurement between input and output images. Experimental results show that the proposed algorithm consistently produces good results.

Spatial Mutual Information and PageRank-Based Contrast Enhancement and Quality-Aware Relative Contrast Measure pdf

 

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