An adaptive enhancement algorithm for low-illumination images based on HSV chromaticity space

Xinglin Yang; Hongyan Chen

doi:10.1117/12.3029864

21 June 2024 An adaptive enhancement algorithm for low-illumination images based on HSV chromaticity space

Xinglin Yang, Hongyan Chen

Proceedings Volume 13167, International Conference on Remote Sensing, Mapping, and Image Processing (RSMIP 2024); 131671I (2024) https://doi.org/10.1117/12.3029864
Event: International Conference on Remote Sensing, Mapping and Image Processing (RSMIP 2024), 2024, Xiamen, China

Abstract

Aiming at the problems of overexposure and poor local contrast in traditional low-light image enhancement algorithms, an adaptive low-light image enhancement algorithm based on HSV chromaticity space is proposed, which firstly converts the input image into RGB to HSV chromaticity space, then extracts components from the converted HSV chromaticity space, and performs convolution operation on the details respectively, and then weight fusion and conversion to RGB image by the convolution operation. Secondly, the weights of the convolved components are fused and converted to RGB images, and finally, the enhanced images are obtained by histogram equalization and contrast-brightness enhancement. The experiments demonstrate that the average PSNR value of this algorithm in 11 different scenes is improved by 44.8%, 31.35%, and 17.86%. In contrast, the SSIM value is reduced by 59.63%, 56.58%, and 25.4%, respectively, compared with the contrast-brightness image enhancement algorithm, the adaptive gamma transform algorithm, and the CLAHE algorithm.

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

Citation Download Citation

Xinglin Yang and Hongyan Chen "An adaptive enhancement algorithm for low-illumination images based on HSV chromaticity space", Proc. SPIE 13167, International Conference on Remote Sensing, Mapping, and Image Processing (RSMIP 2024), 131671I (21 June 2024); https://doi.org/10.1117/12.3029864

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KEYWORDS

RGB color model

Image enhancement

Image fusion

Image processing

Histograms

Detection and tracking algorithms

Image contrast enhancement

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