Color barycenter model based multi-histogram mapping and merging for image enhancement

Qieshi Zhang, Sei Ichiro Kamata

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this paper, the color barycenter model (CBM) based image enhancement method using multihistogram mapping and merging is presented. Generally, histogram analysis based methods are effective for contrast enhancement, but this kind of method is hard to enhance the dark and bright regions efficiently simultaneously, such as the back-light image. To solve this problem, a mapping function is studied for multihistogram mapping to obtain several images with different contrast, and merging them by the best patch selecting of every position. Firstly, using the CBM to calculate the gray component as the input data. Secondly, obtaining several image with different contrast by our mapping function. Thirdly, calculating the gradient feature of the separated patches and selecting the best ones for merging. Finally, using the mix Gaussian filter to smooth the merged image. Based on the proposed approach, enhancement can be achieved for global/local regions under different light conditions. The experimental results show better effectiveness than other methods.

Original languageEnglish
Title of host publicationProceedings of the 13th IAPR International Conference on Machine Vision Applications, MVA 2013
PublisherMVA Organization
Pages238-241
Number of pages4
ISBN (Print)9784901122139
Publication statusPublished - 2013
Event13th IAPR International Conference on Machine Vision Applications, MVA 2013 - Kyoto, Japan
Duration: 2013 May 202013 May 23

Publication series

NameProceedings of the 13th IAPR International Conference on Machine Vision Applications, MVA 2013

Conference

Conference13th IAPR International Conference on Machine Vision Applications, MVA 2013
CountryJapan
CityKyoto
Period13/5/2013/5/23

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Computer Science Applications

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  • Cite this

    Zhang, Q., & Kamata, S. I. (2013). Color barycenter model based multi-histogram mapping and merging for image enhancement. In Proceedings of the 13th IAPR International Conference on Machine Vision Applications, MVA 2013 (pp. 238-241). (Proceedings of the 13th IAPR International Conference on Machine Vision Applications, MVA 2013). MVA Organization.