Abstract—A general framework based on histogram equalizationfor image contrast enhancement is presented. In thisframework, contrast enhancement is posed as an optimizationproblem that minimizes a cost function. Histogram equalization isan effective technique for contrast enhancement. However, a conventionalhistogram equalization (HE) usually results in excessivecontrast enhancement, which in turn gives the processed image anunnatural look and creates visual artifacts. By introducing specificallydesigned penalty terms, the level of contrast enhancementcan be adjusted; noise robustness, white/black stretching andmean-brightness preservation may easily be incorporated into theoptimization. Analytic solutions for some of the important criteriaare presented. Finally, a low-complexity algorithm for contrastenhancement is presented, and its performance is demonstratedagainst a recently proposed method.Index Terms—Histogram equalization, histogram modification,image/video quality enhancement.