Denoising and Contrast Enhancement Fusion Based on White Balance for Underwater Images

被引:1
|
作者
Wei, Chao [1 ,2 ]
Wang, Junfeng [1 ,2 ]
Chen, Guannan [1 ,2 ]
机构
[1] Fujian Normal Univ, Fujian Prov Key Lab Photon Technol, Minist Educ, Key Lab OptoElect Sci & Technol Med, Fuzhou 350007, Peoples R China
[2] Fujian Normal Univ, Fujian Prov Engn Technol Res Ctr Photoelect Sensi, Fuzhou 350117, Fujian, Peoples R China
关键词
Underwater image; contrast enhancement; white-balancing; multiscale fusion;
D O I
10.1117/12.2539429
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
When the scene reached the human eye or other sensor through the underwater medium, the original color property of the object could be basically lost, and the background of most images was blue-green. In this paper, to remove the blue-green color of the underwater image and increase the color contrast of the image, a novel fusion method of two images was proposed. The two images were derived from the filtering denoising result and the contrast enhancement result after white-balancing version of the original degraded image. Then, based on the two images, the associated weight maps were designed to enhance edge texture and color contrast of the output image. Finally, to avoid artifacts in the reconstructed image, we adopted the multiscale fusion strategy to fuse the processed two images. Experiments showed that our algorithm achieved better image contrast and edge sharpness than other methods and obtained better exposure for darker areas of the image.
引用
收藏
页数:5
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