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

Author:

Lu Jian1,Chen Yupeng1,Zou Yuru1,Shen Lixin2

Affiliation:

1. College of Mathematics and Statistics, Shenzhen University, Shenzhen 518060, Guangdong Province, P. R. China

2. Department of Mathematics, Syracuse University, Syracuse, NY 13244, USA

Abstract

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.

Funder

National Natural Science Foundation of China

Natural Science Foundation of Guangdong Province (CN)

National Science Foundation

Publisher

World Scientific Pub Co Pte Lt

Subject

Applied Mathematics,Information Systems,Signal Processing

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