Parameter‐adaptive nighttime image enhancement with multi‐scale decomposition - Shuhang Wang; Jin Zheng; Bo Li (IET Computer Vision, 2016)
As a challenging problem, image enhancement plays an important role in computer vision applications and has been widely studied. As one of the most difficult issues of image enhancement, outdoor nighttime image enhancement suffers from noise amplification easily. To solve this problem, this study proposes a parameter‐adaptive nighttime image enhancement method with multi‐scale decomposition. The main contributions of this work are threefold. First, the authors find out that noises in different scales are various, and their method decomposes an input image into three high‐frequency layers and a background layer accordingly. Second, the authors’ method enhances each high‐frequency layer using adaptive parameters based on the characteristics of noises. Third, the proposed method maps the background layer to make it suitable to present details. Experiment results demonstrate that the proposed method can suppress noises as well as improve details effectively.