Spectrally sensitive wavelet analysis of multispectral imagery for object detection

Samuel Peter Kozaitis; Ty Olmstead

doi:10.1117/12.280600

4 August 1997 Spectrally sensitive wavelet analysis of multispectral imagery for object detection

Samuel Peter Kozaitis, Ty Olmstead

Proceedings Volume 3071, Algorithms for Multispectral and Hyperspectral Imagery III; (1997) https://doi.org/10.1117/12.280600
Event: AeroSense '97, 1997, Orlando, FL, United States

Abstract

We 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 wee processed independently.

Citation Download Citation

Samuel Peter Kozaitis and Ty Olmstead "Spectrally sensitive wavelet analysis of multispectral imagery for object detection", Proc. SPIE 3071, Algorithms for Multispectral and Hyperspectral Imagery III, (4 August 1997); https://doi.org/10.1117/12.280600

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