A new total variation model for restoring blurred and speckle noisy images

被引:6
作者
Lu, Jian [1 ]
Chen, Yupeng [1 ]
Zou, Yuru [1 ]
Shen, Lixin [2 ]
机构
[1] Shenzhen Univ, Coll Math & Stat, Shenzhen 518060, Guangdong, Peoples R China
[2] Syracuse Univ, Dept Math, Syracuse, NY 13244 USA
基金
中国国家自然科学基金; 美国国家科学基金会;
关键词
Speckle noise; deblurring; I-divergence; total variation; MULTIPLICATIVE NOISE; REMOVAL; OPTIMIZATION; RESTORATION; ALGORITHMS;
D O I
10.1142/S0219691317500096
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
In coherent imaging systems, such as the synthetic aperture radar (SAR), the observed images are affected by multiplicative speckle noise. This paper proposes a new variational model based on I-divergence for restoring blurred images with speckle noise. The model minimizes the sum of an I-divergence data fidelity term, a new quadratic penalty term based on the statistical property of the noise and the total-variation regularization term. The existence and uniqueness of a solution of the proposed model with some other characteristics are analyzed. Furthermore, an iterative algorithm is introduced to solve the proposed variational model. Our numerical experiments indicate that the proposed method performs favorably.
引用
收藏
页数:19
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