Detail-Preserving Underexposed Image Enhancement via Optimal Weighted Multi-Exposure Fusion

Abstract

Photographs taken by mobile device usually suffer from loss of details and low visual attraction due to the poor light condition. The enhancement of the underexposed image can effectively solve this problem. However, previous work may inevitably wash out some weak edges and lose details when handling several underexposed images. To deal with these problems, this paper presents a detail-preserving underexposed image enhancement method based on a new optimal weighted multi-exposure fusion mechanism. Providing an input underexposed image, we propose a novel multi-exposure image enhancement method which can generate a multi-exposure image sequence. However, none of these images are good enough, as images with high exposure have good brightness and color information, whereas sharp details are better preserved in the images with lower exposure. In order to preserve details and enhance the blurred edges, we propose to solve an energy function to compute the optimal weight of the three measurements: 1) local contrast; 2) saturation; and 3) exposedness. Then a weighted multi-exposed fusion method is used to generate the final image. Since the proposed approach is computationally light-weight, it is possible to implement it on mobile devices, such as smart phones and compact cameras. Various experiment results validate our new method.