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Image Dehazing Algorithm based on Morphological and Exposure Enhancement

Published: 09 January 2024 Publication History

Abstract

Aiming at the problems of low brightness and information distortion in most image dehazing algorithms, an image dehazing algorithm based on morphological and exposure enhancement was proposed. An initial transmittance is constructed based on dark channel prior, and through a linear model that can estimate haze density, then the transmittance is optimized by morphological closing and opening operations and gradient domain guided filtering. Atmospheric light is obtained by using minimum filter and quad-decomposition algorithm. An image compensation method is proposed to enhance the details of the dehazed image, an exposure enhancement method is used to improve the brightness, and finally converted to the YUV color space and the Y channel is denoised using the BM3D algorithm.

References

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  1. Image Dehazing Algorithm based on Morphological and Exposure Enhancement

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    AAIA '23: Proceedings of the 2023 International Conference on Advances in Artificial Intelligence and Applications
    November 2023
    406 pages
    ISBN:9798400708268
    DOI:10.1145/3603273
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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    Published: 09 January 2024

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    Author Tags

    1. Closing and Opening Operations
    2. Denoised
    3. Exposure Enhancement
    4. Image Compensation
    5. Image Dehazing

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