Publication
Title
Denoising of multispectral images using wavelet thresholding
Author
Abstract
In this paper a denoising technique for multispectral images exploiting interband correlations is proposed. A redundant wavelet transform is applied and denoising is applied by thresholding wavelet coefficients. A scale adaptive threshold value is obtained by exploiting the interband correlation of the signal. First, the coefficients from different bands are multiplied. For these products, the signal and noise probability density functions (pdf) become more separated. The high signal correlation between bands is exploited further by summing these products over all bands, in this way separating noise and signal pdfs even more. The noise pdf of the proposed quantities is derived analytically and from this, a wavelet threshold is derived. The technique is demonstrated to outperform single band wavelet thresholding on multispectral remote sensing images.
Language
English
Source (book)
Proceedings of the SPIE Image and Signal Processing for Remote Sensing IX
Publication
s.l. : 2004
ISBN
0-8194-5121-5
DOI
10.1117/12.510353
Volume/pages
p. 28-35
ISI
000189443300003
Full text (Publisher's DOI)
UAntwerpen
Faculty/Department
Research group
Publication type
Subject
Affiliation
Publications with a UAntwerp address
External links
Web of Science
Record
Identifier
Creation 08.10.2008
Last edited 16.12.2021
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