Linear spectral filtering for feature enhancement in AVIRIS data from the forest ecosystem dynamics flightline in northern Maine

Russell C. Hardie; David M. Moss; Christopher James Peterson

doi:10.1117/12.154697

31 August 1993 Linear spectral filtering for feature enhancement in AVIRIS data from the forest ecosystem dynamics flightline in northern Maine

Russell C. Hardie, David M. Moss, Christopher James Peterson

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Proceedings Volume 1941, Ground Sensing; (1993) https://doi.org/10.1117/12.154697
Event: Optical Engineering and Photonics in Aerospace Sensing, 1993, Orlando, FL, United States

Abstract

In this paper, we investigate the use of linear filtering techniques in the exploitation of hyperspectral imagery. In particular, we focus on applications of the simultaneous diagonalization (SD) filter to hyperspectral image analysis. The SD filter can be designed to enhance a particular feature with a known spectral response pattern and suppress undesired features. The filter is used to enhance surface features in two AVIRIS scenes acquired from the Forest Ecosystem Dynamics (FED) flightline on September 8, 1990. A spectral distance algorithm is also applied to this hyperspectral data to enhance surface targets with similar spectral response patterns. Although no detailed ground information was utilized, targets were selected by image interpretation methods and included an urban/disturbed site, and a wetland bog area, and a northern vegetation type (mixed hardwood). Both the SD filter and the spectral distance algorithm are able to effectively separate these classes of ground features from others.

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Russell C. Hardie, David M. Moss, and Christopher James Peterson "Linear spectral filtering for feature enhancement in AVIRIS data from the forest ecosystem dynamics flightline in northern Maine", Proc. SPIE 1941, Ground Sensing, (31 August 1993); https://doi.org/10.1117/12.154697

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KEYWORDS

Image filtering

Optical filters

Detection and tracking algorithms

Hyperspectral imaging

Image enhancement

Linear filtering

Ecosystems

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