一种基于Dark Channel Prior图像去雾改进算法
An Improved Images Defogging Algorithm Based on Dark Prior Channel

DOI: 10.12677/CSA.2020.1012230, PP. 2189-2196

Keywords: 图像去雾，Dark Channel Prior，滤波，去噪
Image Defogging, Dark Channel Prior, Filter, Denoising

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Abstract:

探测机器人视觉导航中，现场烟雾或者有色气体会直接导致回传的视频图像雾化且充满噪声，图像品质差，影响后续目标检测与跟踪。针对上述问题，本文提出了一种基于Dark Channel Prior图像去雾改进算法，该算法首先对采集到图像进行灰度化预处理，再用滤波器进行去噪处理，有效去除采图像中的噪声，使待处理图像更加平滑，最后使用Dark Channel Prior去雾算法进行去雾处理，得到高品质图像。根据仿真实验表明，本算法能够有效解决图像去雾中的噪声问题，提高传送画面的清晰度，并缩短图像处理时间，时实性更强。
In the vision navigation of detection robot, the scene smoke or colored gas will directly cause the video image to be atomized and filled with noise, and the image quality will be poor, which will affect the subsequent target detection and tracking. In order to solve these problems, an improved fog removal algorithm based on Dark Prior Channel image is proposed in this paper. Firstly, the collected image is pre-processed by grayscale; then the noise is removed by filter; and the noise in the collected image is effectively removed; finally, we use the Dark Channel Prior algorithm to defog the image, and get the high quality image. The simulation results show that the algorithm can effectively solve the noise problem in image defogging, improve the clarity of the transmitted image, shorten the image processing time and improve the real-time performance.

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