An image defog iteration algorithm for optimal estimation of atmospheric light direction

Wang Guan; Rajamohan Parthasarathy; Geng Zexun

doi:10.1117/12.3006087

10 October 2023 An image defog iteration algorithm for optimal estimation of atmospheric light direction

Wang Guan, Rajamohan Parthasarathy, Geng Zexun

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Proceedings Volume 12799, Third International Conference on Advanced Algorithms and Signal Image Processing (AASIP 2023); 1279919 (2023) https://doi.org/10.1117/12.3006087
Event: 3rd International Conference on Advanced Algorithms and Signal Image Processing (AASIP 2023), 2023, Kuala Lumpur, Malaysia

Abstract

In the digital image defog algorithm, restoring a fog-free image relies on calculating transmittance and atmospheric light intensity. However, existing algorithms with division calculations are unstable in low-transmittance scenarios, amplifying noise and degrading image quality. Estimating atmospheric light direction and mode inaccurately also affects the final image. To address these issues, this paper proposes an iterative algorithm. It transforms the imaging model to avoid division calculations and selects the top 0.1% brightest pixels to determine atmospheric light intensity accurately. Experimental results show significant improvements in color fidelity, image clarity, and visual effect. The algorithm achieves 5% increase in color reduction, 13% increase in average gradient, and 16% increase in dark channel prior ratio.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

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Wang Guan, Rajamohan Parthasarathy, and Geng Zexun "An image defog iteration algorithm for optimal estimation of atmospheric light direction", Proc. SPIE 12799, Third International Conference on Advanced Algorithms and Signal Image Processing (AASIP 2023), 1279919 (10 October 2023); https://doi.org/10.1117/12.3006087

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KEYWORDS

Atmospheric modeling

RGB color model

Fiber optic gyroscopes

Signal intensity

Image transmission

Image quality

Image restoration

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