An improved dehazing algorithm using muti-scale weighted transmission fusion and self-adaptive gamma correction

Guangbin Zhou; Lifeng He; Jiqiang Pan; Xiao Zhao; Bin Yao; Yuyan Chao

doi:10.1117/12.2589344

27 January 2021 An improved dehazing algorithm using muti-scale weighted transmission fusion and self-adaptive gamma correction

Guangbin Zhou, Lifeng He, Jiqiang Pan, Xiao Zhao, Bin Yao, Yuyan Chao

Author Affiliations +

Proceedings Volume 11720, Twelfth International Conference on Graphics and Image Processing (ICGIP 2020); 117201T (2021) https://doi.org/10.1117/12.2589344
Event: Twelfth International Conference on Graphics and Image Processing, 2020, Xi'an, China

Abstract

Aiming at the problems of image distortion and detail information loss occurring in recent dehazing algorithms, this paper proposes a dehazing algorithm based on dark channel prior with multi-scale weighted transmission fusion and self-adaptive gamma correction. Firstly, in order to refine the transmission map, a multi-scale weighted transmission fusion strategy with three scales is applied in the transmission estimation step. Then, a self-adaptive gamma correction method is proposed to enhance the contrast performance after applying the multi-scale weighted transmission fusion to image dehazing, and finally get the desired dehazed image. Experimental results demonstrated that the proposed algorithm can not only overcome the problems of image distortion and detail information loss well, but also yields a satisfied performance in comparison with tested similar methods.

Citation Download Citation

Guangbin Zhou, Lifeng He, Jiqiang Pan, Xiao Zhao, Bin Yao, and Yuyan Chao "An improved dehazing algorithm using muti-scale weighted transmission fusion and self-adaptive gamma correction", Proc. SPIE 11720, Twelfth International Conference on Graphics and Image Processing (ICGIP 2020), 117201T (27 January 2021); https://doi.org/10.1117/12.2589344

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