Edge-preserving wavelet thresholding for image denoising

JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS

卷:210

Article; Proceedings Paper

Lazzaro, D.¹  Montefusco, L. B.¹ 

[1] Univ Bologna, Dept Math, I-40126 Bologna, Italy

关键词: image denoising;    dyadic wavelets;    thresholding estimators;    potential functions;   

DOI  :  10.1016/j.cam.2006.10.069

来源: Elsevier

【 摘 要 】

In this paper we consider a general setting for wavelet based image denoising methods. In fact, in both deterministic regularization methods and stochastic maximum a posteriori estimations, the denoised image (f) over cap is obtained by minimizing a functional, which is the sum of a data fidelity term and a regularization term that enforces a roughness penalty on the solution. The latter is usually defined as a sum of potentials, which are functions of a derivative of the image. By considering particular families of dyadic wavelets, we propose the use of new potential functions, which allows us to preserve and restore important image features, such as edges and smooth regions, during the wavelet denoising process. Numerical results are presented, showing the optimal performance of the denoising algorithm obtained. (C) 2006 Elsevier B.V. All rights reserved.

【 授权许可】

Free