Low-light color image enhancement based on NSST

doi:10.19682/j.cnki.1005-8885.2019.0030

中国邮电高校学报(英文) ›› 2019, Vol. 26 ›› Issue (5): 41-48.doi: 10.19682/j.cnki.1005-8885.2019.0030

• Image Processing • 上一篇下一篇

Low-light color image enhancement based on NSST

Wu Xiaochu1, Tang Guijin1 , Liu Xiaohua1, Cui Ziguan1, Luo Suhuai2

1. 南京邮电大学
2. 南京邮电大学通信与信息工程学院

收稿日期:2019-01-31 修回日期:2019-07-29 出版日期:2019-10-31 发布日期:2019-11-06
通讯作者: 唐贵进 E-mail:tanggj@njupt.edu.cn

Low-light color image enhancement based on NSST

Wu Xiaochu1, Tang Guijin1 (?), Liu Xiaohua1, Cui Ziguan1, Luo Suhuai2

Received:2019-01-31 Revised:2019-07-29 Online:2019-10-31 Published:2019-11-06

摘要/Abstract

摘要： In order to improve the visibility and contrast of low-light images and better preserve the edge and details of images, a new low-light color image enhancement algorithm is proposed in this paper. The steps of the proposed algorithm are described as follows. First, the image is converted from the red, green and blue (RGB) color space to the hue , saturation and value (HSV) color space, and the histogram equalization (HE) is performed on the value component. Next, non-subsampled shearlet transform (NSST) is used on the value component to decompose the image into a low frequency sub-band and several high frequency sub-bands. Then, the low frequency sub-band and high frequency sub-bands are enhanced respectively by Gamma correction and improved guided image filtering (IGIF), and the enhanced value component is formed by inverse NSST transform. Finally, the image is converted back to the RGB color space to obtain the enhanced image. Experimental results show that the proposed method not only significantly improves the visibility and contrast, but also better preserves the edge and details of images.

关键词: non-subsampled shearlet transform, guided image filtering, low-light image enhancement, the HSV color space

Abstract: In order to improve the visibility and contrast of low-light images and better preserve the edge and details of images, a new low-light color image enhancement algorithm is proposed in this paper. The steps of the proposed algorithm are described as follows. First, the image is converted from the red, green and blue (RGB) color space to the hue , saturation and value (HSV) color space, and the histogram equalization (HE) is performed on the value component. Next, non-subsampled shearlet transform (NSST) is used on the value component to decompose the image into a low frequency sub-band and several high frequency sub-bands. Then, the low frequency sub-band and high frequency sub-bands are enhanced respectively by Gamma correction and improved guided image filtering (IGIF), and the enhanced value component is formed by inverse NSST transform. Finally, the image is converted back to the RGB color space to obtain the enhanced image. Experimental results show that the proposed method not only significantly improves the visibility and contrast, but also better preserves the edge and details of images.

Key words: non-subsampled shearlet transform, guided image filtering, low-light image enhancement, the HSV color space

Wu Xiaochu, Tang Guijin, Liu Xiaohua, Cui Ziguan, Luo Suhuai. Low-light color image enhancement based on NSST[J]. The Journal of China Universities of Posts and Telecommunications, 2019, 26(5): 41-48.

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Low-light color image enhancement based on NSST

Low-light color image enhancement based on NSST

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