Abstract
In this paper, a novel cluster validation method based on one-class support vector machines (OC-SVM )is presented. Also it is proposed to segment hyperspectral images with subtractive clustering accompanied by phase correlation. The proposed cluster validity measure is based on the power of spectral discrimination (PWSD) measure and utilizes the advantage of the inherited cluster contour definition feature of OC-SVM. Basically this method provides a solution to the estimation of the correct number of clusters which is an important problem in hyperspectral image segmentation.
Keywords
Hyperspectral imaging
Support vector machine
Pattern recognition (psychology)
Artificial intelligence
Cluster analysis
Computer science
Measure (data warehouse)
Segmentation
Image segmentation
Class (philosophy)
Cluster (spacecraft)
Feature vector
k-means clustering
Data mining
Subject Areas
Remote-Sensing Image Classification
·Media Technology ·Physical Sciences
Spectroscopy and Chemometric Analyses
·Analytical Chemistry ·Physical Sciences
Advanced Chemical Sensor Technologies
·Biomedical Engineering ·Physical Sciences
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