Abstract
In the state of the art, grayscale image enhancement algorithms are typically adopted for enhancement of RGB color images captured with low or non-uniform illumination. As these methods are applied to each RGB channel independently, imbalanced inter-channel enhancements (color distortion) can often be observed in the resulting images. On the other hand, images with non-uniform illumination enhanced by the retinex algorithm are prone to artifacts such as local blurring, halos, and over-enhancement. To address these problems, an improved RGB color image enhancement method is proposed for images captured under non-uniform illumination or in poor visibility, based on weighted guided image filtering (WGIF). Unlike the conventional retinex algorithm and its variants, WGIF uses a surround function instead of a Gaussian filter to estimate the illumination component; it avoids local blurring and halo artifacts due to its anisotropy and adaptive local regularization. To limit color distortion, RGB images are first converted to HSI (hue, saturation, intensity) color space, where only the intensity channel is enhanced, before being converted back to RGB space by a linear color restoration algorithm. Experimental results show that the proposed method is effective for both RGB color and grayscale images captured under low exposure and non-uniform illumination, with better visual quality and objective evaluation scores than from comparator algorithms. It is also efficient due to use of a linear color restoration algorithm.
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Acknowledgements
This work was supported by the National Natural Science Foundation of China (Grant No. 2019YFB1405000), and the National Natural Science Basic Research Plan Program of Shannxi, China (Grant Nos. 2019JM-162 and 2019JM-348).
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Qi Mu is an associate professor at Xi’an University of Science and Technology, China. Her research interests are in computer vision, digital image manipulation, and enterprise information construction.
Xinyue Wang is a postgraduate student at Xi’an University of Science and Technology. Her research interests are in digital image processing and computer vision.
Yanyan Wei received her master degree from Xi’an University of Science and Technology in 2019. Her research interests are in digital image processing.
Zhanli Li is a professor at Xi’an University of Science and Technology, China. His research interests are in intelligent information processing, computer graphics and image processing technology, visual computing and visualization, intelligent computing, and big data analysis.
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Mu, Q., Wang, X., Wei, Y. et al. Low and non-uniform illumination color image enhancement using weighted guided image filtering. Comp. Visual Media 7, 529–546 (2021). https://doi.org/10.1007/s41095-021-0232-x
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DOI: https://doi.org/10.1007/s41095-021-0232-x