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We present a new haze removal algorithm based on attention map-guided multi-scale image processing. The proposed method is based on the frequency-domain coefficient correction of a set of images followed by their fusion based on the Laplacian pyramid. A new stage is presented in obtaining a local-global estimate of high-contrast images, also used in the attention map-guided fusion model. The algorithm consists of the following steps: gamma correction with different gamma parameters; the weight map calculation by multiplying the saturation, contrast, and attention for each image; decomposition of the weight map into a Gaussian pyramid; 3-D block-rooting enhancement; decomposition of images after 3-D block-rooting and gamma correction into the Laplacian pyramid; merging by multiplying multi-scale images and weights. The experiment results on the dataset D-HAZE confirmed the high efficiency of the proposed enhancement method compared to the state-of-the-art techniques for industrial inspection systems.
(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.
V. Voronin,N. Gapon,M. Zhdanova,E. Semenishchev, andA. Zelensky
"Attention map-guided multi-scale haze removal method for industrial inspection system", Proc. SPIE 12769, Optical Metrology and Inspection for Industrial Applications X, 127691R (27 November 2023); https://doi.org/10.1117/12.2690890
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V. Voronin, N. Gapon, M. Zhdanova, E. Semenishchev, A. Zelensky, "Attention map-guided multi-scale haze removal method for industrial inspection system," Proc. SPIE 12769, Optical Metrology and Inspection for Industrial Applications X, 127691R (27 November 2023); https://doi.org/10.1117/12.2690890