In this paper, we study the problem of image denoising by using an adaptive lifting scheme. Such a scheme can adapt itself well to the analyzed signal, which allows to keep important information for denoising applications. However, it results in a non-isometric transform which can be an important limitation as most of the denoising approaches rely on the estimation of the noise energy in the subbands. In a previous work, it has been shown how to evaluate the subband energies of an uncorrelated signal, in the wavelet domain when using such an adaptive scheme. Based on this previous work, we propose in this paper an estimation of the noise energies in the subband and use it to perform image denoising. Experimental results illustrate that this approach is more effective, in image denoising, than the classical non adaptive lifting schemes both considering perceptual and non perceptual image quality measures. ©2010 IEEE.

Image denoising by adaptive lifting schemes

Cagnazzo M.;
2010

Abstract

In this paper, we study the problem of image denoising by using an adaptive lifting scheme. Such a scheme can adapt itself well to the analyzed signal, which allows to keep important information for denoising applications. However, it results in a non-isometric transform which can be an important limitation as most of the denoising approaches rely on the estimation of the noise energy in the subbands. In a previous work, it has been shown how to evaluate the subband energies of an uncorrelated signal, in the wavelet domain when using such an adaptive scheme. Based on this previous work, we propose in this paper an estimation of the noise energies in the subband and use it to perform image denoising. Experimental results illustrate that this approach is more effective, in image denoising, than the classical non adaptive lifting schemes both considering perceptual and non perceptual image quality measures. ©2010 IEEE.
2010
2010 2nd European Workshop on Visual Information Processing, EUVIP2010
978-1-4244-7288-8
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11577/3471541
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