ABSTRACT Images captured under low-illumination environments often impose difficulties in revealing objects of interest. An effective approach, Optimum Shift-and-Weighted Brightness Mapping, is here proposed that can optimally enhance the image for higher brightness, information content, and colour vividness. Specifically, the input-output brightness mapping is determined by a shifted spline curve and a larger amplification is allowed for low-brightness pixels. A weighting function is further applied such that high brightness pixels are preserved. The final enhanced image is obtained by inserting the extracted high frequency components from the original input to the brightness boosted image. The algorithm is adaptive to image contents where parameters are optimized using the efficient golden section search instead of relying on user specified coefficients. Experimental results, from a large set of test images, showed that better quality images could be obtained on a variety of low-illumination scenarios as compared to several recent approaches.

中文翻译：

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用于低照度图像恢复的最佳移位和加权亮度映射

摘要 在低照度环境下捕获的图像通常难以揭示感兴趣的对象。这里提出了一种有效的方法，即最优移位和加权亮度映射，它可以最佳地增强图像以获得更高的亮度、信息内容和色彩鲜艳度。具体来说，输入输出亮度映射由移动的样条曲线决定，允许对低亮度像素进行更大的放大。进一步应用加权函数以保留高亮度像素。最终的增强图像是通过将从原始输入中提取的高频分量插入到亮度增强图像中获得的。该算法适用于图像内容，其中使用有效的黄金分割搜索而不是依赖于用户指定的系数来优化参数。来自大量测试图像的实验结果表明，与最近的几种方法相比，可以在各种低照度场景下获得更好质量的图像。