Multi-histogram mapping and fusion based image contrast enhancement

Qieshi Zhang, Seiichiro Kamata

Research output: Contribution to journalArticlepeer-review


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
Issue number1
Publication statusPublished - 2015


  • 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


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