Feature discrimination using multiband classification techniques

Jim Ivey; Scott R. Fairchild; James R. Peterson; Charles Greg Stahl

doi:10.1117/12.50812

1 December 1991 Feature discrimination using multiband classification techniques

Jim Ivey, Scott R. Fairchild, James R. Peterson, Charles Greg Stahl

Proceedings Volume 1567, Applications of Digital Image Processing XIV; (1991) https://doi.org/10.1117/12.50812
Event: San Diego, '91, 1991, San Diego, CA, United States

Abstract

Multiband synthetic aperture radar (SAR) is beginning to join the suite of spectral data sets available for feature discrimination and classification. For myriad practical applications, it is useful to quantify how well multiband SAR performs on its own, and how well it performs compared to and in conjunction with visual and infrared (IR) wavelength band sets. This paper examines these issues in the context of land use determination for a rural area in California's Central Valley, using multifrequency, multipolarization imagery from the NASA/JPL Airborne Imaging Radar (AIR). A supervised classification of the major terrain types is used to assess the performance of the AIR bands. Also, the best band combinations for feature discrimination are selected from a combined band set containing AIR, visual wavelength, and IR bands.

Citation Download Citation

Jim Ivey, Scott R. Fairchild, James R. Peterson, and Charles Greg Stahl "Feature discrimination using multiband classification techniques", Proc. SPIE 1567, Applications of Digital Image Processing XIV, (1 December 1991); https://doi.org/10.1117/12.50812

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