De-Hazing and Enhancement Methods for Underwater and Low-Light Images

被引：0
|
作者：
Liu K. [1 ]
Li X. [1 ]
机构：
[1] College of Computer Science and Engineering, Shandong University of Science and Technology, Qingdao
来源：
Guangxue Xuebao/Acta Optica Sinica | 2020年 / 40卷 / 19期
关键词：
Edge details; Guided filtering; Image de-hazing; Image enhancement; Image processing; Underexposed image;
D O I：
10.3788/AOS202040.1910003
中图分类号：
T [工业技术];
学科分类号：
08 ;
摘要：
This paper proposes a de-hazing and enhancement method for underwater and low-light images to effectively enhance the images. Multi-scale Retinex color recovery (MSRCR) and guided filtering methods are used for de-hazing; super-resolution convolutional neural network (SRCNN) and non-subsampled contour transform (NSCT) technology are combined to enhance the image. Experimental results show that compared with similar existing image processing methods, this method can effectively improve the image exposure, and at the same time, it can sufficiently preserve and enhance the color saturation and edge texture details of images. It uses a unified method to achieve the enhancement of underwater and low-light images, and the results are more efficient, which has a good visual effect. © 2020, Chinese Lasers Press. All right reserved.
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