Backlit traffic scene image enhancement based on foreground and background characteristics

Ronggui Ma; Zizhong Wei; Yixu He; Xunyan Huang; Mingxiao Ma

doi:10.1117/12.2689157

31 July 2023 Backlit traffic scene image enhancement based on foreground and background characteristics

Ronggui Ma, Zizhong Wei, Yixu He, Xunyan Huang, Mingxiao Ma

Proceedings Volume 12747, Third International Conference on Optics and Image Processing (ICOIP 2023); 127471P (2023) https://doi.org/10.1117/12.2689157
Event: Third International Conference on Optics and Image Processing (ICOIP 2023), 2023, Hangzhou, China

Abstract

Due to the low foreground brightness and distorted background brightness of traffic backlight images, a technique of fusing LIME and improved histogram equalization is proposed to eliminate the backlight phenomenon in images. Firstly, the input image is segmented into two parts, foreground and background, using the maximum interclass variance method. Then LIME method is used globally for the backlit image to enhance the foreground brightness while maintaining the color distortion, and only the foreground part of the processed image is retained. Then the pixel value distribution of the background part is calculated separately, and the global histogram equalization results on the three RGB channels are mapped one by one to the corresponding limited interval, which improves the contrast of the background. Finally, the Canny operator is used to detect the black edges at the front background stitching, and three adaptive filtering templates are generated based on the black edges to perform step-by-step mean filtering on the black edges, eliminating the black edges and improving the visual quality of the image. The average metrics of the proposed method on the laboratory selfconstructed CHD_B dataset are, respectively, NIQE of 5.37, BRISQUE of 47.74, average gradient of 0.79, information entropy of 6.61, and average running time of 11.38s, which are synthetically better than the current backlight image enhancement methods and have better visual quality and visibility

Citation Download Citation

Ronggui Ma, Zizhong Wei, Yixu He, Xunyan Huang, and Mingxiao Ma "Backlit traffic scene image enhancement based on foreground and background characteristics", Proc. SPIE 12747, Third International Conference on Optics and Image Processing (ICOIP 2023), 127471P (31 July 2023); https://doi.org/10.1117/12.2689157

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KEYWORDS

Image processing

Image enhancement

Backlighting

Image segmentation

Histograms

Image quality

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