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10.1109/ICASSP.2017.7952379guideproceedingsArticle/Chapter ViewAbstractPublication PagesConference Proceedingsacm-pubtype
research-article

Retinex-based perceptual contrast enhancement in images using luminance adaptation

Published: 05 March 2017 Publication History

Abstract

In this paper, we propose retinex-based perceptual contrast enhancement in images using luminance adaptation. We use the retinex theory to decompose an image into illumination and reflectance layers, and adopt luminance adaptation to handle the illumination layer which causes detail loss. First, we obtain the illumination layer using adaptive Gaussian filtering to remove halo artifacts. Then, we adaptively remove illumination of the illumination layer in the multi-scale retinex (MSR) process based on luminance adaptation to preserve details. Finally, we perform contrast enhancement on the MSR result. Experimental results demonstrate that the proposed method successfully enhances contrast in images while keeping textures in highlight regions.

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Cited By

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  • (2020)Low Light Image Enhancement Algorithm Based on Retinex and Dehazing ModelProceedings of the 6th International Conference on Robotics and Artificial Intelligence10.1145/3449301.3449777(84-90)Online publication date: 20-Nov-2020

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        2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
        Mar 2017
        6527 pages

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        Published: 05 March 2017

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        • (2020)Low Light Image Enhancement Algorithm Based on Retinex and Dehazing ModelProceedings of the 6th International Conference on Robotics and Artificial Intelligence10.1145/3449301.3449777(84-90)Online publication date: 20-Nov-2020

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