Cross-Entropy Histogram Equalization

被引：0

作者：

Roopaei, Mehdi Senior ^{[1
]}

Agaian, Sos ^{[1
]}

Shadaram, Mehdi ^{[1
]}

Hurtado, Frank ^{[1
]}

机构：

[1] Univ Texas San Antonio, Dept Elect & Comp Engn, San Antonio, TX USA

来源：

2014 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN AND CYBERNETICS (SMC) | 2014年

关键词：

Cross-entropy; Brightness/Darkness decomposition; Image enhancement; Histogram Equalization; CONTRAST ENHANCEMENT; BRIGHTNESS;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper introduces a novel cross-entropy Histogram Equalization method. The new algorithm is based on separating the density spectrum of an image and then minimizing the so-called Cross-Entropy between the brightness and darkness components. Cross-entropy is used to measure the information-theoretic distance between the image's brightness and darkness. Experimental results show that the cross-entropy histogram equalization method has better performance than Bi-histogram equalization and its modified weighted form.

引用

页码：158 / 163

页数：6

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