基于示例的图像对比度增强

Zhiyuan Zhou, Xiaokang Yang, Li Chen, Guangtao Zhai, Wenjun Zhang
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引用次数: 1

摘要

本文提出了一种新的基于实例的对比度增强算法。该方法通过从样本图像的直方图中学习一些重要的先验信息来增强对比度。实验结果表明,本文提出的基于实例的离散拉伸(ExDS)对比度增强算法可以有效地提高图像的对比度。由于基于示例的学习过程,ExDS算法的输出图像比传统的基于直方图均衡化的方法更自然。所提出的ExDS算法还可以扩展到旧电影修复中的对比度校正以及图像和视频后期制作中的色调映射。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Example-based image contrast enhancement
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.
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