Backlit image enhancement based on foreground extraction

Minghua Zhao; Danni Cheng; Li Wang

doi:10.1117/12.2589408

27 January 2021 Backlit image enhancement based on foreground extraction

Minghua Zhao, Danni Cheng, Li Wang

Proceedings Volume 11720, Twelfth International Conference on Graphics and Image Processing (ICGIP 2020); 1172019 (2021) https://doi.org/10.1117/12.2589408
Event: Twelfth International Conference on Graphics and Image Processing, 2020, Xi'an, China

Abstract

To deal with the problem of low foreground brightness in the backlit image, a novel backlit image enhancement method is proposed in this paper. First, K nearest neighbors (KNN) matting is used on the original images. By dividing the lower-brightness part into the foreground and marking the contour as the unknown area, the trimap of the image is defined, and the opacity of each pixel is calculated in the marked foreground. Second, logarithmic transformation method is used to enhance the extracted foreground image, and the brightness can be improved to different degrees by setting the base number. Finally, the original image is combined with the enhanced foreground part to obtain the synthesized image, which is more natural and the phenomenon of insufficient or excessive enhancement is avoided. Experimental results show that the influence of backlight conditions on image can be eliminated by the proposed approach, and the image quality is improved significantly and is superior to the conventional and the cutting-edge algorithms.

Citation Download Citation

Minghua Zhao, Danni Cheng, and Li Wang "Backlit image enhancement based on foreground extraction", Proc. SPIE 11720, Twelfth International Conference on Graphics and Image Processing (ICGIP 2020), 1172019 (27 January 2021); https://doi.org/10.1117/12.2589408

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