A Novel Evaluation Standard Combining Gini-index and Variation Coefficient for Double Plateaus Histogram Equalization

Image contrast enhancement or boosting is normally referred to as one of the most crucial tasks in image processing, and histogram equalization (HE) is one of the most pervasive methods applied to address this task. HE and its variants have been proven a simple and effective technique. However, no one consistent image quality evaluation standard has been built for them, not to say other relevant approaches. In other words, it is lack of enough attention to image quality evaluation for contrast enhancement algorithms. The authors proposed a novel evaluation standard combining Gini-index and variation coefficient. They verified the effectiveness of the proposed evaluation standard especially for double plateaus histogram equalization (DPHE) algorithm. Their experimental results showed that the proposed objective standard could provide an additional objective basis for the quality evaluation of DPHE, which may be extended to pervasive image enhancement algorithms.