Retinex-Based Fast Algorithm for Low-Light Image Enhancement

We proposed the Retinex-based fast algorithm (RBFA) to achieve low-light image enhancement in this paper, which can restore information that is covered by low illuminance. The proposed algorithm consists of the following parts. Firstly, we convert the low-light image from the RGB (red, green, blue)...

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Bibliographic Details
Published in:Entropy (Basel, Switzerland) Switzerland), 2021-06, Vol.23 (6), p.746
Main Authors: Liu, Shouxin, Long, Wei, He, Lei, Li, Yanyan, Ding, Wei
Format: Article
Language:English
Subjects:
Algorithms
Color
Dynamic range
gamma correction
HSV color space
Illuminance
Image contrast
Image enhancement
Image restoration
Light
Linear functions
low-light image
Methods
Retinex
Retinex (algorithm)
Saturation (color)
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Summary:We proposed the Retinex-based fast algorithm (RBFA) to achieve low-light image enhancement in this paper, which can restore information that is covered by low illuminance. The proposed algorithm consists of the following parts. Firstly, we convert the low-light image from the RGB (red, green, blue) color space to the HSV (hue, saturation, value) color space and use the linear function to stretch the original gray level dynamic range of the V component. Then, we estimate the illumination image via adaptive gamma correction and use the Retinex model to achieve the brightness enhancement. After that, we further stretch the gray level dynamic range to avoid low image contrast. Finally, we design another mapping function to achieve color saturation correction and convert the enhanced image from the HSV color space to the RGB color space after which we can obtain the clear image. The experimental results show that the enhanced images with the proposed method have better qualitative and quantitative evaluations and lower computational complexity than other state-of-the-art methods.
ISSN:1099-4300
1099-4300
DOI:10.3390/e23060746