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Proceedings Paper

Wavelet-based noise reduction in multispectral imagery
Author(s): Abdullah A. Basuhail; Samuel Peter Kozaitis
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Paper Abstract

We used a 3-D wavelet-based denoising method to reduce the noise from multispectral imagery. In our approach, we compared denoising of different bands of a multispectral image using a 2-D denoising technique, by which the wavelet coefficients corresponding to each band were denoised independent of each band, and a 3-D denoising technique by which the wavleet coefficients were denoised by involving all bands in thresholding the wavelet coefficients. Due to the high correlation of the multispectral imagery data along the wavelength axis, the noise can be easily reduced by applying the wavelet transform along the wavelength direction. Our results showed that the 3-D denoising approach improved the overall SNR of a noisy multispectral imagery over the 2-D denoising approach, due to the correlation between the different bands.

Paper Details

Date Published: 2 July 1998
PDF: 7 pages
Proc. SPIE 3372, Algorithms for Multispectral and Hyperspectral Imagery IV, (2 July 1998); doi: 10.1117/12.312604
Show Author Affiliations
Abdullah A. Basuhail, Florida Institute of Technology (Saudi Arabia)
Samuel Peter Kozaitis, Florida Institute of Technology (United States)


Published in SPIE Proceedings Vol. 3372:
Algorithms for Multispectral and Hyperspectral Imagery IV
Sylvia S. Shen; Michael R. Descour, Editor(s)

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