Automated scene-derived normalization of spectral imagery for subpixel classification

Robert L. Huguenin; Mo-Hwa Wang; Mark A. Karaska; Kelly E. Roberts

doi:10.1117/12.328098

16 October 1998 Automated scene-derived normalization of spectral imagery for subpixel classification

Robert L. Huguenin, Mo-Hwa Wang, Mark A. Karaska, Kelly E. Roberts

Proceedings Volume 3438, Imaging Spectrometry IV; (1998) https://doi.org/10.1117/12.328098
Event: SPIE's International Symposium on Optical Science, Engineering, and Instrumentation, 1998, San Diego, CA, United States

Abstract

Changing illumination and atmospheric conditions hamper the automated analysis of spectral imagery. Applied Analysis Inc. developed an environmental correction module as part of its subpixel classifier software. This module derives atmospheric and sun angle correction factors directly from an image without the use of predictive models. Subpixel occurrences of dark and bright surface features are used to characterize atmospheric radiance, atmospheric attenuation and sensor transfer functions. A significant component of each pixel used to derive this information can be unwanted surface reflectance from sun glint, sky illumination, or other solar-illuminated terrain materials. These spectral contributions distort the accurate assessment of atmospheric radiance, atmospheric attenuation and sensor transfer functions. By working at a subpixel level, the subpixel classifier software is able to more accurately derive these factors, resolution in improved environmental correction.

Citation Download Citation

Robert L. Huguenin, Mo-Hwa Wang, Mark A. Karaska, and Kelly E. Roberts "Automated scene-derived normalization of spectral imagery for subpixel classification", Proc. SPIE 3438, Imaging Spectrometry IV, (16 October 1998); https://doi.org/10.1117/12.328098

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