SCENS: Simultaneous Contrast Enhancement and Noise Suppression for Low-Light Images

Imaging in low-light conditions often suffers from degradations, such as low visibility, low contrast, and noticeable noise, which significantly reduces the performance of various vision-based applications. While various methods are proposed to enhance image contrast, inevitable noise is also amplified notably. Consequently, it is highly desired to take both contrast enhancement and noise suppression into consideration simultaneously. In this article, we propose a novel and unified framework SCENS to simultaneously enhance contrast and suppress noise for low-light images. An observed low-light image is decomposed into illumination, reflectance, and noise components. More specifically, the illumination is estimated using the second-order total generalized variation to preserve the spatial smoothness and the overall structure. In contrast, the piecewise continuity and fine detail of reflectance are maintained by minimizing the residual of gradients between the reflectance and the scene. Experimental results demonstrate the effectiveness of the proposed SCENS on contrast enhancement and noise mitigation. In addition, both subjective and objective comparisons with state-of-the-art algorithms indicate the superiority of the proposed method.