Adaptive histogram analysis for image enhancement

Qieshi Zhang*, Hiroshi Inaba, Sei Ichiro Kamata

*Corresponding author for this work

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

7 Citations (Scopus)

Abstract

One image processing application is to reconstruct the original scene from the low quality images. Considering the idea histogram distribution can reflect good vision effect. So many histogram analyzing based methods have been studied recently. However, some methods require users to set some parameters or condition, and cannot get the optimal results automatically. To overcome those short come, this paper presents an Adaptive Histogram Separation and Mapping (AHSM) method for Backlight image enhancement. First, we separate the histogram by binary tree structure with the proposed Adaptive Histogram Separation Unit (AHSU). And then mapping the Low Dynamic Range (LDR) histogram partition into High Dynamic Range (HDR). By doing this, the excessive or scarcity enhancement can be avoid. The experimental results show that the proposed method can gives better enhancement results, also compared with some histogram analyzing based methods and get better results.

Original languageEnglish
Title of host publicationProceedings - 4th Pacific-Rim Symposium on Image and Video Technology, PSIVT 2010
Pages408-413
Number of pages6
DOIs
Publication statusPublished - 2010 Dec 1
Event4th Pacific-Rim Symposium on Image and Video Technology, PSIVT 2010 - Singapore, Singapore
Duration: 2010 Nov 142010 Nov 17

Publication series

NameProceedings - 4th Pacific-Rim Symposium on Image and Video Technology, PSIVT 2010

Conference

Conference4th Pacific-Rim Symposium on Image and Video Technology, PSIVT 2010
Country/TerritorySingapore
CitySingapore
Period10/11/1410/11/17

ASJC Scopus subject areas

  • Computer Graphics and Computer-Aided Design
  • Computer Vision and Pattern Recognition
  • Human-Computer Interaction
  • Software

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