%X A new subspace approach is proposed for enhancement of image corrupted by additive white noise. In subspace filtering methods, the noisy image is decomposed into two orthogonal subspaces, a signal subspace and a noise subspace. This decomposition is possible under the assumption of a low-rank model for image and the availability of an estimate of the noise covariance matrix. It is shown in this paper that the proposed image restoration method performs better than the Wiener filtering and wavelet denoising techniques. © 2010 IEEE.
%K Additive white noise; Karhunen-Love transform; Noise covariance; Noise covariance matrix; Noise subspace; Noisy image; Orthogonal subspaces; Signal sub-space; Subspace approach; Subspace based methods; Subspace filtering; Wavelet de-noising techniques; Wiener filtering, Covariance matrix; Image reconstruction; Principal component analysis; Restoration, White noise
%R 10.1109/APCCAS.2010.5774861
%D 2010
%L scholars855
%J IEEE Asia-Pacific Conference on Circuits and Systems, Proceedings, APCCAS
%O cited By 2; Conference of 2010 Asia Pacific Conference on Circuit and System, APCCAS 2010 ; Conference Date: 6 December 2010 Through 9 December 2010; Conference Code:85160
%C Kuala Lumpur
%A N. Yahya
%A N.S. Kamel
%A A.S. Malik
%T A subspace approach for restoring image corrupted by white noise
%P 128-131