基于Retinex模型的暗位视觉图像增强算法

Lijuan Xiang, Lingyun Gao, Ying Zhao, Qin Zhang, Zhiqiang Zhao
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引用次数: 0

摘要

暗域视觉图像增强存在过度增强和光环伪影等问题,本文基于视网膜理论,提出了一种用于增强图像的照度图估计方法。具体来说,我们分别提取了Max-RGB和Y通道图像作为全局和局部初始照明映射。然后,我们改进了加权引导滤波器,以减少晕影。接下来,我们对初始照明地图进行加权平均,改进加权引导滤波和伽马校正,作为最终的照明地图。最后,根据视网膜理论对光照图进行校正,得到增强结果。实验表明,与现有的几种方法相比,该方法可以获得更小的亮度失真和减少光晕伪影。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Scotopic Vision Image Enhancement Algorithm Based on Retinex Model
Scotopic vision image enhancement has problems of over-enhancement and halo artifacts, based on retinex theory, this article proposes illumination map estimate method to enhancement image to solve those problems. Specifically, we extracted the image of Max-RGB and Y channel as global and local initial illumination map respectively. Then, we improved weighted guided filter to reduce halo artifacts. Next, we refined the initial illumination maps with weighted average, improved weighted guided filtering and gamma correction, as the final illumination map. Finally, the enhanced result is obtained by the corrected illumination map according to retinex theory. Experiments shown that the method can obtain results with less lightness distortion and reduce halo artifacts compared with that of several state-of-the-art methods.
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