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Mathematical Problems in Engineering
Volume 2012, Article ID 242043, 14 pages
Research Article

A Multiplicative Noise Removal Approach Based on Partial Differential Equation Model

College of Mathematics and Computational Science, Shenzhen University, Shenzhen 518060, China

Received 26 February 2012; Accepted 23 March 2012

Academic Editor: Ming Li

Copyright © 2012 Bo Chen et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Multiplicative noise, also known as speckle noise, is signal dependent and difficult to remove. Based on a fourth-order PDE model, this paper proposes a novel approach to remove the multiplicative noise on images. In practice, Fourier transform and logarithm strategy are utilized on the noisy image to convert the convolutional noise into additive noise, so that the noise can be removed by using the traditional additive noise removal algorithm in frequency domain. For noise removal, a new fourth-order PDE model is developed, which avoids the blocky effects produced by second-order PDE model and attains better edge-preserve ability. The performance of the proposed method has been evaluated on the images with both additive and multiplicative noise. Compared with some traditional methods, experimental results show that the proposed method obtains superior performance on different PSNR values and visual quality.