Multi-histogram mapping and fusion based image contrast enhancement

Qieshi Zhang, Seiichiro Kamata

Research output: Contribution to journalArticle

Abstract

In this paper, a contrast enhancement method called Multi-Histogram Mapping and Fusion (MHMF) is proposed for color images. Histogram analysis based method has been successfully applied to contrast enhancement in some applications, but they are hard to enhance the dark and bright regions simultaneously for back-light images. To solve this problem, the color barycenter model (CBM) is extended to separate the color image into lightness and chroma components. Then multi-histogram mapping (MHM) is used to map the lightness component of one single color image into several new lightness components with different contrast. These new components are divided into several patches and the best patches are selected by calculating image entropy. Finally, the selected patches are fused to create the enhanced image, and mix-Gaussian filter is applied to remove the sharp transition. The experimental results show the effectiveness of proposed method comparing with other state-of-the-art methods.

Original languageEnglish
Pages (from-to)2-11
Number of pages10
JournalITE Transactions on Media Technology and Applications
Volume3
Issue number1
Publication statusPublished - 2015

Fingerprint

Fusion reactions
Color
Entropy

Keywords

  • Color Barycenter Model (CBM)
  • Image Contrast Enhancement
  • Image Fusion
  • Mix-Gaussian Filter
  • Multi-Histogram Mapping (MHM)

ASJC Scopus subject areas

  • Computer Graphics and Computer-Aided Design
  • Signal Processing
  • Media Technology

Cite this

Multi-histogram mapping and fusion based image contrast enhancement. / Zhang, Qieshi; Kamata, Seiichiro.

In: ITE Transactions on Media Technology and Applications, Vol. 3, No. 1, 2015, p. 2-11.

Research output: Contribution to journalArticle

@article{1246758093034343940369ded20ce2d4,
title = "Multi-histogram mapping and fusion based image contrast enhancement",
abstract = "In this paper, a contrast enhancement method called Multi-Histogram Mapping and Fusion (MHMF) is proposed for color images. Histogram analysis based method has been successfully applied to contrast enhancement in some applications, but they are hard to enhance the dark and bright regions simultaneously for back-light images. To solve this problem, the color barycenter model (CBM) is extended to separate the color image into lightness and chroma components. Then multi-histogram mapping (MHM) is used to map the lightness component of one single color image into several new lightness components with different contrast. These new components are divided into several patches and the best patches are selected by calculating image entropy. Finally, the selected patches are fused to create the enhanced image, and mix-Gaussian filter is applied to remove the sharp transition. The experimental results show the effectiveness of proposed method comparing with other state-of-the-art methods.",
keywords = "Color Barycenter Model (CBM), Image Contrast Enhancement, Image Fusion, Mix-Gaussian Filter, Multi-Histogram Mapping (MHM)",
author = "Qieshi Zhang and Seiichiro Kamata",
year = "2015",
language = "English",
volume = "3",
pages = "2--11",
journal = "ITE Transactions on Media Technology and Applications",
issn = "2186-7364",
publisher = "Institute of Image Information and Television Engineers",
number = "1",

}

TY - JOUR

T1 - Multi-histogram mapping and fusion based image contrast enhancement

AU - Zhang, Qieshi

AU - Kamata, Seiichiro

PY - 2015

Y1 - 2015

N2 - In this paper, a contrast enhancement method called Multi-Histogram Mapping and Fusion (MHMF) is proposed for color images. Histogram analysis based method has been successfully applied to contrast enhancement in some applications, but they are hard to enhance the dark and bright regions simultaneously for back-light images. To solve this problem, the color barycenter model (CBM) is extended to separate the color image into lightness and chroma components. Then multi-histogram mapping (MHM) is used to map the lightness component of one single color image into several new lightness components with different contrast. These new components are divided into several patches and the best patches are selected by calculating image entropy. Finally, the selected patches are fused to create the enhanced image, and mix-Gaussian filter is applied to remove the sharp transition. The experimental results show the effectiveness of proposed method comparing with other state-of-the-art methods.

AB - In this paper, a contrast enhancement method called Multi-Histogram Mapping and Fusion (MHMF) is proposed for color images. Histogram analysis based method has been successfully applied to contrast enhancement in some applications, but they are hard to enhance the dark and bright regions simultaneously for back-light images. To solve this problem, the color barycenter model (CBM) is extended to separate the color image into lightness and chroma components. Then multi-histogram mapping (MHM) is used to map the lightness component of one single color image into several new lightness components with different contrast. These new components are divided into several patches and the best patches are selected by calculating image entropy. Finally, the selected patches are fused to create the enhanced image, and mix-Gaussian filter is applied to remove the sharp transition. The experimental results show the effectiveness of proposed method comparing with other state-of-the-art methods.

KW - Color Barycenter Model (CBM)

KW - Image Contrast Enhancement

KW - Image Fusion

KW - Mix-Gaussian Filter

KW - Multi-Histogram Mapping (MHM)

UR - http://www.scopus.com/inward/record.url?scp=84952047386&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84952047386&partnerID=8YFLogxK

M3 - Article

AN - SCOPUS:84952047386

VL - 3

SP - 2

EP - 11

JO - ITE Transactions on Media Technology and Applications

JF - ITE Transactions on Media Technology and Applications

SN - 2186-7364

IS - 1

ER -