Underwater image restoration algorithm to restrain correlated noise

被引：0

作者：

Xiao, Yihan ^{[1
]}

Pang, Yongjie ^{[2
]}

Zhao, Lanfei ^{[1
]}

机构：

[1] College of Information and Communication Engineering, Harbin Engineering University, Harbin

[2] Science and Technology on Underwater Vehicle Laboratory, Harbin Engineering University, Harbin

来源：

Harbin Gongcheng Daxue Xuebao/Journal of Harbin Engineering University | 2015年 / 36卷 / 06期

关键词：

Correlated noise; Gradient method; Underwater image; Variational model;

D O I：

10.3969/j.issn.1006-7043.201404045

中图分类号：

学科分类号：

摘要：

The traditional algorithm cannot get rid of the influence of correlated noise on underwater images. In view of this, this paper proposes a restoration algorithm to restrain the correlated noises of underwater images by establishing a variational model based on the theory of maximum a posteriori estimation that represents convex property. In the variational model, the probability distribution of noise is guaranteed via the item of Bayesian restraint. Meanwhile the property of spatial continuity is satisfied via the Markov constraint. The gradient method is employed to obtain the optimal solution of the variational model, i.e. the restoration image without correlated noise. Experimental results show the correlated noise is eliminated by the proposed algorithm effectively; the restoration images present an excellent visual effect. ©, 2015, Editorial Board of Journal of HEU. All right reserved.

引用

页码：841 / 846

页数：5