Share Email Print
cover

Proceedings Paper

Fast multiscale regularization and segmentation of hyperspectral imagery via anisotropic diffusion and algebraic multigrid solvers
Author(s): Julio M. Duarte-Carvajalino; Guillermo Sapiro; Miguel Vélez--Reyes; Paul Castillo
Format Member Price Non-Member Price
PDF $14.40 $18.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

This paper presents an algorithm that generates a scale-space representation of hyperspectral imagery using Algebraic Multigrid (AMG) solvers. The scale-space representation is obtained by solving with AMG a vector-valued anisotropic diffusion equation, with the hyperspectral image as its initial condition. AMG also provides the necessary structure to obtain a hierarchical segmentation of the image. The scale space representation of the hyperspectral image can be segmented in linear time complexity. Results in the paper show that improved segmentation is achieved. The proposed methodology to solve vector PDEs can be used to extend a number of techniques currently being developed for the fast computation of geometric PDEs and its application for the processing of hyperspectral and multispectral imagery.

Paper Details

Date Published: 7 May 2007
PDF: 12 pages
Proc. SPIE 6565, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XIII, 656512 (7 May 2007); doi: 10.1117/12.721036
Show Author Affiliations
Julio M. Duarte-Carvajalino, Univ. of Puerto Rico, Mayagüez (United States)
Guillermo Sapiro, Univ. of Minnesota (United States)
Miguel Vélez--Reyes, Univ. of Puerto Rico, Mayagüez (United States)
Paul Castillo, Univ. of Puerto Rico, Mayagüez (United States)


Published in SPIE Proceedings Vol. 6565:
Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XIII
Sylvia S. Shen; Paul E. Lewis, Editor(s)

© SPIE. Terms of Use
Back to Top