Backlight Image Enhancement by Fusing Images of Global and Local Region Brightness

Backlight is one of the main causes of degrading image quality, which limits its applications to a large extent. To address the issues of brightness reduction and loss of detail information of backlight image, this paper proposes an image enhancement algorithm by fusing global and local brightness enhancements. Through the color estimation model (CEM) based on global statistics, the detail information of backlight image can be well restored. To eliminate the fuzzy effect on dark region of backlight image by CEM, the brightness preserving color estimation model (BPCEM) is presented. Unlike CEM, it is also shown that the problem of over enhancement on local region can be avoided by BPCEM. By taking advantages of both CEM and BPCEM model, an adaptive fusion method based on block information entropy is proposed. Thus, good balance between CEM and BPCEM can be made. Experimental results show that the proposed method has achieved competitive performance.