Automatic local contrast enhancement using adaptive histogram adjustment
Yi‐Chong Zeng · 2009
This paper presents the adaptive histogram adjustment (AHA) to improve image contrast. The proposed method is achieved based on the concepts of weighted histogram separation and gray-level grouping. It not only improves the contrast of the local detail but also solves group density and blocky effect which occur at the under-quantization problem of weighted histogram separation. Moreover, the adaptive histogram adjustment can prevent the contrast over-enhancement of conventional adaptive-based approach. The experimental results show that AHA has good contrast sensitivity, and it is compared with the five existing approaches, such as, histogram equalization, adaptive histogram equalization, weighted histogram separation, adaptive weighted histogram separation and gray-level grouping.