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Open Access

A Multivariate Thresholding Technique for Image Denoising Using Multiwavelets

EURASIP Journal on Advances in Signal Processing20052005:297296

Received: 20 January 2004

Published: 31 May 2005


Multiwavelets, wavelets with several scaling functions, offer simultaneous orthogonality, symmetry, and short support, which is not possible with ordinary (scalar) wavelets. These properties make multiwavelets promising for signal processing applications, such as image denoising. The common approach for image denoising is to get the multiwavelet decomposition of a noisy image and apply a common threshold to each coefficient separately. This approach does not generally give sufficient performance. In this paper, we propose a multivariate thresholding technique for image denoising with multiwavelets. The proposed technique is based on the idea of restoring the spatial dependence of the pixels of the noisy image that has undergone a multiwavelet decomposition. Coefficients with high correlation are regarded as elements of a vector and are subject to a common thresholding operation. Simulations with several multiwavelets illustrate that the proposed technique results in a better performance.

Keywords and phrases

multiwaveletsimage denoisingmultivariate thresholding

Authors’ Affiliations

Department of Electrical and Computer Engineering, University of Delaware, Newark, USA
Electrical and Electronics Engineering Department, Boğaziçi University, Bebek, Turkey


© Bala and Ertüzün 2005