Local-to-Global Adaptive Image Enhancement Algorithm

In traditional histogram modification technologies, there is a problem that the algorithm can't deal with the local features and global information simultaneously. In this paper, we proposed a new adaptive image enhancement algorithm which used both the local features and global information. Image enhancement was divided into local enhancement and global enhancement. In the step of local enhancement, the pixel neighborhood information and the ratio between local contrast and global contrast were used as the gamma value of a power transformation. This process increased the local contrast and the luminance of the dark region. Then, the region similarity histogram was developed in global enhancement to suppress the noise and avoid the over-enhancement. The experiments show that the proposed algorithm is better than traditional image enhancement methods, and it can improve the face detection ratio under complex illumination.