30 October 2009 Multiscale graph cut based classification of urban hyperspectral imagery
Author Affiliations +
Proceedings Volume 7494, MIPPR 2009: Multispectral Image Acquisition and Processing; 74941U (2009) https://doi.org/10.1117/12.834010
Event: Sixth International Symposium on Multispectral Image Processing and Pattern Recognition, 2009, Yichang, China
Abstract
This paper proposes a novel multiscale graph cut based analysis framework for the supervised classification of hyperspectral imagery. This framework is aimed at obtaining accurate and reliable maps by properly considering the spatial-context information. It is made up of two main blocks: 1) a feature-extraction block exploits an object-oriented analysis and representation of hyperspectral imagery that is obtained by multiscale graph cut (MGC) based segmentation; 2) a classifier, based on support vector machines (SVMs), capable of analyzing hyperdimensional feature spaces. Experimental results confirm the effectiveness of the proposed system for the analysis of hyperspectral imagery.
© (2009) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Xin Yu, Ruiqin Niu, Yi Wang, Ke Wu, "Multiscale graph cut based classification of urban hyperspectral imagery", Proc. SPIE 7494, MIPPR 2009: Multispectral Image Acquisition and Processing, 74941U (30 October 2009); doi: 10.1117/12.834010; https://doi.org/10.1117/12.834010
PROCEEDINGS
9 PAGES


SHARE
Back to Top