Contrast-Controllable Image Enhancement Based on Limited Histogram

To address the technical shortcomings of conventional histogram equalization (HE), such as over-enhancement and artifacts, we propose a histogram-constrained contrast-tunable HE technique for digital image enhancement. Firstly, input is partitioned into two parts, main constrained histogram, by cumulative probability density threshold; second, redistributed equally in whole grayscale range; finally, nonlinearity mapped to histogram. The experimental averages show that values metrics, information entropy MS-SSIM, processed algorithms this paper, are more accurate compared other six excellent algorithms.