DCT with alternating least squares post-processing for variational defogging

Long Ma; Mingliang Li

doi:10.1117/12.3035316

19 July 2024 DCT with alternating least squares post-processing for variational defogging

Long Ma, Mingliang Li

Proceedings Volume 13213, International Conference on Image Processing and Artificial Intelligence (ICIPAl 2024); 132131X (2024) https://doi.org/10.1117/12.3035316
Event: International Conference on Image Processing and Artificial Intelligence (ICIPAl2024), 2024, Suzhou, China

Abstract

Image defogging methods for traditional physical models produce artifactual effects while removing haze because the coupling of different color channels is not considered. To solve this problem, an alternating least squares post-processing method for variational defogging is proposed. On the basis of the variational model for haze removal, The dehazed image is processed by alternating least squares, which is based on the atmospheric scattering model, and the discrete cosine image transform is used to process the image through transform the image into the frequency domain, and the smoothness of the function is realized by the linear combination of the first few terms of the discrete cosine transform. The transmittance of the three RGB color channels is coupled to effectively remove the artifacts present in the image, and experiments are conducted in the LIVE Image Defogging database to compare with the classical defogging methods. The results of our experiment show that the present algorithm not only reduces the artifacts of the image, but also improves the image quality. It shows that the method in this paper has excellent effect of removing fog.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Long Ma and Mingliang Li "DCT with alternating least squares post-processing for variational defogging", Proc. SPIE 13213, International Conference on Image Processing and Artificial Intelligence (ICIPAl 2024), 132131X (19 July 2024); https://doi.org/10.1117/12.3035316

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KEYWORDS

Image quality

Image processing

Atmospheric modeling

Fiber optic gyroscopes

RGB color model

Image restoration

Image transmission

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