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:2019,28(6):165-171
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基于暗原色先验的低照度视频增强算法
(1.中国科学院大学, 北京 100049;2.
中国科学院 沈阳计算技术研究所, 沈阳 110168)
Low Lighting Video Enhancement Algorithm Based on Dark Channel Prior
(1.University of Chinese Academy of Sciences, Beijing 100049, China;2.
Shenyang Institute of Computing Technology, Chinese Academy of Sciences, Shenyang 110168, China)
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投稿时间:2018-12-10    修订日期:2018-12-29
中文摘要: 在低照度条件下,视频质量总是不容乐观.对比度低,边缘细节不清晰,亮度低等情况会给视频后续处理带来很多不必要的麻烦.针对这种情况,本文提出了一种改进的基于暗原色先验的低照度视频增强算法.首先将输入的低照度图像取反,再对该图像进行去雾操作.大气光值由输入图像的暗通道最大值估计,同时,利用快速导向滤波计算并优化透射率,实现了保边降噪.最后,通过再次取反图像得到增强后的图像.透过实验结果证实,该算法能有效增强低照度图像的对比度,突出图像边缘的细节,提高图像的亮度,有效增强低照度图像.
Abstract:The quality of video with low lighting is always pessimistic. Many images have low contrast, blurry edges, and low brightness. These situations will bring inconvenience to subsequent processing. For solving these problems, an improved algorithm named low lighting video enhancement algorithm based on dark channel prior is presented. Firstly, the input image is inverted, and then dehazed. Atmospheric light is estimated by the maximum value of dark channel in input image. At the same time, the refractive index t is calculated and optimized with fast guided filter, which help realizing edge-ware and denoising. Finally, the image is inverted again. The result shows that the proposed algorithm can enhance the contrast of low lighting image, improve the brightness, and highlight the details of the edges of the image.
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刘峰,王信佳,于波,徐福龙.基于暗原色先验的低照度视频增强算法.计算机系统应用,2019,28(6):165-171
LIU Feng,WANG Xin-Jia,YU Bo,XU Fu-Long.Low Lighting Video Enhancement Algorithm Based on Dark Channel Prior.COMPUTER SYSTEMS APPLICATIONS,2019,28(6):165-171

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