A Hybrid L2 −LP Variational Model For Single Low-Light Image Enhancement With Bright Channel Prior
Gang Fu, Lian Duan, Chunxia Xiao · 2019
In this paper, we consider and study the norm variable and propose a hybrid L2-Lpvariational model with bright channel prior based on Retinex to decompose an observed image into a reflectance layer and an illumination layer. Different from the existing methods, our proposed model can preserve the reflectance layer with more fine details while enforcing the illumination layer to be texture-less, avoiding the texture-copy problem. Moreover, for solving our non-linear optimization, we adopt an alternating minimization scheme to find the optimal. Finally, we test our algorithm on a large number of images and the experimental results illustrate that the proposed method has achieved the better result than other state-of-the-art methods both qualitatively and quantitatively.