A Probabilistic Method for Image Enhancement With Simultaneous Illumination and Reflectance Estimation

作者：Xueyang Fu, Yinghao Liao, Delu Zeng, Yue Huang, Xiao–Ping Zhang, Xinghao Ding · 发表于：IEEE Transactions on Image Processing · 年份：2015 · DOI：10.1109/tip.2015.2474701 · 被引用次数：467 · 研究领域：Image Enhancement Techniques、Color Science and Applications、Advanced Image Processing Techniques

In this paper, a new probabilistic method for image enhancement is presented based on a simultaneous estimation of illumination and reflectance in the linear domain. We show that the linear domain model can better represent prior information for better estimation of reflectance and illumination than the logarithmic domain. A maximum a posteriori (MAP) formulation is employed with priors of both illumination and reflectance. To estimate illumination and reflectance effectively, an alternating direction method of multipliers is adopted to solve the MAP problem. The experimental results show the satisfactory performance of the proposed method to obtain reflectance and illumination with visually pleasing enhanced results and a promising convergence rate. Compared with other testing methods, the proposed method yields comparable or better results on both subjective and objective assessments.