Open AccessA novel detail weighted histogram equalization method for brightness preserving image enhancement based on partial statistic and global mapping model
Author(s) -
Li Yu,
Yuan Zifeng,
Zheng Kun,
Jia Luheng,
Guo Huaqiu,
Pan Hongyuan,
Guo Jingjing,
Huang Lidong
Publication year - 2022
Publication title -
iet image processing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.401
H-Index - 45
eISSN - 1751-9667
pISSN - 1751-9659
DOI - 10.1049/ipr2.12567
Subject(s) - histogram equalization , histogram , artificial intelligence , computer science , adaptive histogram equalization , histogram matching , image histogram , brightness , pattern recognition (psychology) , pixel , statistic , image quality , image (mathematics) , computer vision , mathematics , image texture , image processing , statistics , physics , optics
Abstract Histogram equalization (HE) is a classic and widely used image contrast enhancement algorithm for its good performance and high efficiency. However, over‐enhancement caused by high peak in the histogram affects the subjective quality of the image processed by HE to a large extent. In this paper, a detail weighted histogram equalization (DWHE) method is proposed based on a novel histogram modification (HM) model named partial statistic and global mapping (PSGM) to alleviate high peak and suppress over‐enhancement. Moreover, the authors implement a refined version of gamma correction (GC) named texture enhancement function (TEF) on high‐frequency images to reduce the noise amplification effect. At last, the authors propose a novel adaptively weighted pixel‐level image fusion method to further reduce the phenomenon of over‐enhancement and improve brightness distribution. Both subjective and quantitative evaluations are conducted on images containing a variety of scenes. Compared with several state‐of‐the‐art image enhancement methods, the proposed framework obtained generally the best performance in aspects of both subjective appearance and objective evaluation indices. Therefore, it is proved that the proposed methods can effectively alleviate the over‐enhancement, enrich image details, and efficiently improve the visual quality while preserving the brightness of the image.