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dc.contributor.authorKozaitis, S.P.
dc.contributor.authorOlmstead, Ty
dc.date.accessioned2017-10-05T13:09:23Z
dc.date.available2017-10-05T13:09:23Z
dc.date.issued1997-08-04
dc.identifier.citationKozaitis, S. P., & Olmstead, T. (1997). Spectrally sensitive wavelet analysis of multispectral imagery for object detection. Paper presented at the Proceedings of SPIE - the International Society for Optical Engineering, , 3071 2-11.en_US
dc.identifier.urihttp://hdl.handle.net/11141/1745
dc.descriptionCorrelation detectors, Object recognition, Signal to noise ratio, Wavelet transformsen_US
dc.description.abstractWe used a 3D wavelet denoising method to reduce noise from multispectral imagery so that small objects may be more readily detected. Our approach exploits the correlation between bands typically present in multispectral imagery. Using our approach, the resulting image generally consists of a weighted sum of both spectral bands and spatial frequencies. We found that we could generally increase the SNR of a multispectral image more than if the spectral bands were processed independently.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.titleSpectrally sensitive wavelet analysis of multispectral imagery for object detectionen_US
dc.typeConference Proceedingen_US
dc.identifier.doi10.1117/12.280600


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