Wavelet-based noise reduction in multispectral imagery

Abdullah A. Basuhail; Samuel Peter Kozaitis

doi:10.1117/12.312604

2 July 1998 Wavelet-based noise reduction in multispectral imagery

Abdullah A. Basuhail, Samuel Peter Kozaitis

Proceedings Volume 3372, Algorithms for Multispectral and Hyperspectral Imagery IV; (1998) https://doi.org/10.1117/12.312604
Event: Aerospace/Defense Sensing and Controls, 1998, Orlando, FL, United States

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.

Citation Download Citation

Abdullah A. Basuhail and Samuel Peter Kozaitis "Wavelet-based noise reduction in multispectral imagery", Proc. SPIE 3372, Algorithms for Multispectral and Hyperspectral Imagery IV, (2 July 1998); https://doi.org/10.1117/12.312604

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