Enhancement Algorithm for Low-lighting Images Based on Physical Model and Boundary Constraint
CHEN Yong① ZHAN Di① LIU Huanlin②
①(Key Laboratory of Industrial Internet of Things and Network Control, Ministry of Education, Chongqing University of Posts and Telecommunications, Chongqing 400065, China) ②(Key Laboratory of Optical Fiber Communication Technology, Chongqing University of Posts and Telecommunications, Chongqing 400065, China)
Abstract：The aim of this paper is to achieve a low-lighting image enhancement method by using the similarity between fog image and inverted low illumination image. The transmittance estimation of the pseudo-fog image is estimated by the improved boundary constraint, and then it is optimized. Based on the formation principle of pseudo fog, the light intensity of pseudo fog map is estimated by using the brightness component of low illumination image. The enhanced pseudo fog image is reversed to obtain the enhanced low illumination image. Extensive experimental results using natural low-lighting images indicate that the proposed method perform better than contemporary algorithms in terms of several metrics, including the intensity, the contrast. The proposed algorithm can effectively suppress the wrong phenomenon caused by enhanced with low complexity.
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CHEN Yong, ZHAN Di, LIU Huanlin. Enhancement Algorithm for Low-lighting Images Based on Physical Model and Boundary Constraint. JEIT, 2017, 39(12): 2962-2969.
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