An adaptive weak light image enhancement method

Wencheng Wang, Zhenxue Chen, Xiaohui Yuan, Fengnian Guan
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引用次数: 5

Abstract

In this paper, an adaptive method is proposed to address the problems of over-enhancement of weak light image enhancing and adaptivity of parameter settings based on local gamma transform and illumination-reflection model. In which the source image is converted from RGB color space into the YUV color space firstly, and the illumination distribution of the scene is extracted by using a guided filtering function. Then, an adaptive local gamma transform is designed to perform enhancement on the illumination component and the dynamic range of gray-scale is expanded. Finally, the image is changed from YUV space to RGB space. Experimental results shows that the proposed algorithm can not only effectively improve the visual effect of the uneven light image but also reveal more detailed information in dark regions.
一种自适应弱光图像增强方法
本文提出了一种基于局部伽马变换和光照-反射模型的自适应方法,以解决弱光图像增强的过度增强和参数设置的自适应问题。该方法首先将源图像从RGB色彩空间转换为YUV色彩空间,并利用引导滤波函数提取场景的光照分布。然后,设计自适应局部伽马变换对光照分量进行增强,扩大灰度动态范围;最后,将图像从YUV空间转换为RGB空间。实验结果表明,该算法不仅能有效改善不均匀光图像的视觉效果,而且能在暗区显示更详细的信息。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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