Skip to Main Content
In this paper, a novel example-based contrast enhancement algorithm is proposed. The proposed approach enhances the contrast by learning some important informative priors from the histogram of the example image. The experimental results indicate that the proposed Example-based Dist-Stretched (ExDS) contrast enhancement algorithm can boost the image contrast effectively. And thanks to the example-based learning process, the output images from the ExDS algorithm have more natural looking than those of traditional histogram equalization based methods. The proposed ExDS algorithm can also be extended to the applications of contrast correction for old film restoration as well as tone mapping for image and video post-productions.