Literature DB >> 27409434

Hue-preserving and saturation-improved color histogram equalization algorithm.

Ki Sun Song, Hee Kang, Moon Gi Kang.   

Abstract

In this paper, an algorithm is proposed to improve contrast and saturation without color degradation. The local histogram equalization (HE) method offers better performance than the global HE method, whereas the local HE method sometimes produces undesirable results due to the block-based processing. The proposed contrast-enhancement (CE) algorithm reflects the characteristics of the global HE method in the local HE method to avoid the artifacts, while global and local contrasts are enhanced. There are two ways to apply the proposed CE algorithm to color images. One is luminance processing methods, and the other one is each channel processing methods. However, these ways incur excessive or reduced saturation and color degradation problems. The proposed algorithm solves these problems by using channel adaptive equalization and similarity of ratios between the channels. Experimental results show that the proposed algorithm enhances contrast and saturation while preserving the hue and producing better performance than existing methods in terms of objective evaluation metrics.

Entities:  

Year:  2016        PMID: 27409434     DOI: 10.1364/JOSAA.33.001076

Source DB:  PubMed          Journal:  J Opt Soc Am A Opt Image Sci Vis        ISSN: 1084-7529            Impact factor:   2.129


  1 in total

1.  A Pyramid Architecture-Based Deep Learning Framework for Breast Cancer Detection.

Authors:  Dong Sui; Weifeng Liu; Jing Chen; Chunxiao Zhao; Xiaoxuan Ma; Maozu Guo; Zhaofeng Tian
Journal:  Biomed Res Int       Date:  2021-10-01       Impact factor: 3.411

  1 in total

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