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An image haze removal algorithm based on multiscale block-rooting processing has been developed for removing haze/fog from an image based on frequency-domain coefficient correction of a set of images followed by their fusion based on the Laplacian pyramid. A new stage is proposed in obtaining a local-global estimate of high-contrast images, which are also used in the general fusion model. The proposed block-based multiscale enhancement method base on 3-D block-rooting multiscale transform domain technique, comprising: finding similar blocks in the image by block-matching; block-grouping for different block sizes; applying 3-D block-matching parametric image enhancement; calculating the quality measure of enhancement; optimizing parameters of image enhancement method through the quality measure of enhancement; fusing different enhanced images. To test the performance of the proposed algorithm, the public database O-HAZE is used.
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V. Voronin, O. Tokareva, N. Gapon, I. Naumov, A. Zelensky, E. Semenishchev, "Image haze removal using block-based multiscale enhancement method," Proc. SPIE 12526, Multimodal Image Exploitation and Learning 2023
, 125260X (15 June 2023); https://doi.org/10.1117/12.2666558