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http://dx.doi.org/10.5573/ieie.2014.51.2.124

Backlit Region Detection Using Adaptively Partitioned Block and Fuzzy C-means Clustering for Backlit Image Enhancement  

Kim, Nahyun (Dept. of Image Engineering, Graduate School of Advanced Image Science, Multimedia, and Film, Chung-Ang University)
Lee, Seungwon (Dept. of Image Engineering, Graduate School of Advanced Image Science, Multimedia, and Film, Chung-Ang University)
Paik, Joonki (Dept. of Image Engineering, Graduate School of Advanced Image Science, Multimedia, and Film, Chung-Ang University)
Publication Information
Journal of the Institute of Electronics and Information Engineers / v.51, no.2, 2014 , pp. 124-132 More about this Journal
Abstract
In this paper, we present a novel backlit region detection and contrast enhancement method using fuzzy C-means clustering and adaptively partitioned block based contrast stretching. The proposed method separates an image into both dark backlit and bright background regions using adaptively partitioned blocks based on the optimal threshold value computed by fuzzy logic. The detected block-wise backlit region is refined using the guided filter for removing block artifacts. Contrast stretching algorithm is then applied to adaptively enhance the detected backlit region. Experimental results show that the proposed method can successfully detect the backlit region without a complicated segmentation algorithm and enhance the object information in the backlit region.
Keywords
대비 개선;영상 개선;유도 필터;역광 보상;
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