Share Email Print
cover

Proceedings Paper

Robust spatial and spectral feature extraction for multispectral and hyperspectral imagery
Author(s): Jorge E. Pinzon; Susan L. Ustin; Claudia M. Castaneda; John F. Pierce; L. A. Costick
Format Member Price Non-Member Price
PDF $14.40 $18.00

Paper Abstract

We present a hierarchical classification technique that discriminates broad categories of surface materials in terms of ground true features, such as water, vegetation, and soils from spectral information. Subsequently, we further discriminate these materials and extract finer ground features, like chemistries, peculiar to each. The interaction at various scales of the 3D spatial and the spectral domains is decomposed by using wavelet tools to address scale dependencies in the spatial domain, a robust spectral unmixing technique, called Hierarchical Foreground Background Analysis (HFBA) along the spectral axis. HFBA sequentially derives a series of weighting vectors discriminating features at different levels of detection: (1) constituent materials, (2) types within constituents, and (3) chemistries peculiar to each type. Our goal is two-fold. First, we present the combination of HFBA and wavelets as a supervised classification technique validating the categories imposed by the supervised classification, and manifesting clusters which can refine the classification at different scales. Second, we identify spectral redundancies between hyperspectral and multispectral information, studying mixture at different spatial/spectral resolutions and assess whether targeted features may be extracted as efficiently from multispectral data as they could be from hyperspectral data. Results on AVIRIS and simulated MODIS data illustrate the robustness and effectivity of the technique.

Paper Details

Date Published: 2 July 1998
PDF: 12 pages
Proc. SPIE 3372, Algorithms for Multispectral and Hyperspectral Imagery IV, (2 July 1998); doi: 10.1117/12.312601
Show Author Affiliations
Jorge E. Pinzon, Univ. of California/Davis (United States)
Susan L. Ustin, Univ. of California/Davis (United States)
Claudia M. Castaneda, Univ. of California/Davis (United States)
John F. Pierce, K-T Tech, Inc. (United States)
L. A. Costick, Univ. of California/Davis (United States)


Published in SPIE Proceedings Vol. 3372:
Algorithms for Multispectral and Hyperspectral Imagery IV
Sylvia S. Shen; Michael R. Descour, Editor(s)

© SPIE. Terms of Use
Back to Top