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dc.contributor.authorBasuhail, Abdullah A.
dc.contributor.authorKozaitis, S.P.
dc.date.accessioned2017-10-05T13:11:29Z
dc.date.available2017-10-05T13:11:29Z
dc.date.issued1998-07-02
dc.identifier.citationBasuhail, A. A., & Kozaitis, S. P. (1998). Wavelet-based noise reduction in multispectral imagery. Paper presented at the Proceedings of SPIE - the International Society for Optical Engineering, , 3372 234-240.en_US
dc.identifier.urihttp://hdl.handle.net/11141/1750
dc.descriptionDenoising, Multispectral, Three-dimensional wavelet transformen_US
dc.description.abstractWe 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 wavelet 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.en_US
dc.language.isoen_USen_US
dc.rightsThis published article is made available in accordance with publishers policy. It may be subject to U.S. copyright law.en_US
dc.rights.urihttp://spie.org/publications/journals/guidelines-for-authors#Terms_of_Useen_US
dc.titleWavelet-based noise reduction in multispectral imageryen_US
dc.typeConference Proceedingen_US
dc.identifier.doi10.1117/12.312604


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