A wavelet-denoising approach for removing background noise in medical images

Author

Hua, Zhong ; Chong, Man-Nang

Author_Institution

Sch. of Appl. Sci., Nanyang Technol. Univ., Singapore

fYear

1997

fDate

9-12 Sep 1997

Firstpage

980

Abstract

This paper presents a new noise removal algorithm for removing the background noise in medical images. In this algorithm, techniques such as noise suppression in the wavelet transform (WT) domain, sub-domain noise detection (SND) and adaptive least squared error clustering (ALSEC) are proposed. Extensive tests have shown that the proposed algorithm is robust; poor SNR medical images can be de-noised effectively

Keywords

adaptive signal processing; biomedical NMR; cardiology; image recognition; interference suppression; least squares approximations; medical image processing; noise; wavelet transforms; ALSEC; SND; WT; adaptive least squared error clustering; background noise; magnetic resonance imaging; medical images; noise removal algorithm; noise suppression; poor SNR medical images; sub-domain noise detection; wavelet transform domain; wavelet-denoising approach; Background noise; Biomedical imaging; Clustering algorithms; Detection algorithms; Image reconstruction; Noise robustness; Pixel; Wavelet coefficients; Wavelet domain; Wavelet transforms;

fLanguage

English

Publisher

ieee

Conference_Titel

Information, Communications and Signal Processing, 1997. ICICS., Proceedings of 1997 International Conference on

Print_ISBN

0-7803-3676-3

Type

conf

DOI

10.1109/ICICS.1997.652126

Filename

652126