Abstract
Dust weather is increasingly frequent, seriously affecting the quality of outdoor surveillance video images. In dusty weather, due to the presence of a large amount of dust particles in the air, these particles selectively absorb and scatter light, resulting in blurred details of the captured image, low contrast and clarity, and serious color shift problems. In order to solve the above problems, this paper proposes a dust image enhancement method based on YUV space. The method firstly transfers the RGB dust image to the YUV space, and for the first time innovatively uses the color components U, V to correct the color shift in the YUV space, Then, the improved MSR(Multi-scale Retinex) algorithm is used to process the Y component to reduce the influence of scattered light in the air to improve the image clarity. Next, the Y component is stretched linearly to display the Y component on the display screen. Finally, the Y component is enhanced again with CLAHE(contrast-limited histogram equalization), improving the overall contrast and enhancing the detail of the image. The experimental results show that, compared with the contrast algorithm, the proposed algorithm has natural color, clear and bright details, good overall visual effect and real-time performance.
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