%K Additive white noise; De-noising techniques; Image noise reduction; Prewhitening; Residual noise; Root mean square errors; Structural similarity; Subspace based; Time domain; WIENER filters, Image processing; Mean square error; White noise, Time domain analysis
%C Kuala Lumpur
%O cited By 1; Conference of 2011 2nd IEEE International Conference on Signal and Image Processing Applications, ICSIPA 2011 ; Conference Date: 16 November 2011 Through 18 November 2011; Conference Code:88668
%P 221-226
%D 2011
%L scholars1553
%X In this paper a subspace based technique is proposed for removal of additive white noise in images. The method is based on Time-Domain constrained (TDC) estimator in which the residual noise energy is kept below a threshold while minimizing the signal distortion. The denoising technique employed prewhitening method prior to the subspace filter which is proven to give remarkable results. Experiments were carried out on noise-free images corrupted with simulated additive white noise. The results indicate that the proposed methods provide performance better than Wiener filter in terms of the root mean square error and structural similarity index measure. © 2011 IEEE.
%R 10.1109/ICSIPA.2011.6144166
%A N. Yahya
%A N.S. Kamel
%A A.S. Malik
%J 2011 IEEE International Conference on Signal and Image Processing Applications, ICSIPA 2011
%T A subspace-based technique for image noise reduction