Low-light image enhancement using variational optimization-based retinex model
Seonhee Park, Soohwan Yu, Byeongho Moon, Seungyong Ko, Joonki Paik · IEEE Transactions on Consumer Electronics · 2017
This paper presents an optimization-based low-light image enhancement method using spatially adaptive l2-norm based Retinex model. The proposed method adaptively enforces the regularization parameter using the spatially adaptive weight map, which is generated using the bright channel prior (BCP) and local variance map. Since the proposed weight map assigns the smaller weight value at the bright and edge region, the proposed method can perform weak noise reduction to preserve the edges and textures. In addition, the simplified version of the proposed method is presented using the FFT and quantized weight values for the application to consumer devices. Experimental results show that the proposed method can provide better enhanced result without the l2-norm minimization artifacts at the low computational cost.