Space-adaptive spectral analysis of hyperspectral imagery

Luciano Alparone; Fabrizio Argenti; Michele Dionisio; Luca Facheris

doi:10.1117/12.463090

13 March 2003 Space-adaptive spectral analysis of hyperspectral imagery

Luciano Alparone, Fabrizio Argenti, Michele Dionisio, Luca Facheris

Proceedings Volume 4885, Image and Signal Processing for Remote Sensing VIII; (2003) https://doi.org/10.1117/12.463090
Event: International Symposium on Remote Sensing, 2002, Crete, Greece

Abstract

The aim of this paper is investigating the use of overcomplete bases for the representation of hyperspectral image data. The idea is building an overcomplete basis starting from several orthogonal or non-orthogonal bases and picking up a set of vectors fitting pixel spectra to the largest extent. A common technique to select the most representative elements of a signal is Matching Pursuit (MP). This technique is analogous to the Mixed-Transform Analysis (MTA) and has been successfully used to represent speech and images. The main problems in using MTA for hyperspectral data analysis are: (1) choice of bases that potentially convey the maximum of spectral information; (2) calculation of projections in the non-orthogonal representation. A large variety of bases has been taken into consideration, including several types of wavelets with compact support. An iterative approach is used to find the coefficients of the linear combination of vectors, so that the residual function has minimum energy. The computational cost is extrmeely high when a large set of data is to be processed. To encompass computational constraints, a reduced data set (RDS) is produced by applying the projection pursuit technique to each of the square blocks in which the input hyperspectral iamge is partitioned based on a spatial homogeneity criterion. Then MTA is applied to the RDS to find out a non-orthogonal frame capable to represent such data through waveforms selected to best match spectral features. Experimental results carried out on the hyperspectral data AVIRIS Moffett Field '97 show the joint use of different bases, including wavelet bases, may be preferable to a unique orthogonal basis in terms of energy compaction, was well as of significance of the outcome components.

Citation Download Citation

Luciano Alparone, Fabrizio Argenti, Michele Dionisio, and Luca Facheris "Space-adaptive spectral analysis of hyperspectral imagery", Proc. SPIE 4885, Image and Signal Processing for Remote Sensing VIII, (13 March 2003); https://doi.org/10.1117/12.463090

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available