Spectral-Spatial Hyperspectral Image Classification Using Subspace-Based Support Vector Machines and Adaptive Markov Random Fields

Spectral-Spatial Hyperspectral Image Classification Using Subspace-Based Support Vector Machines and Adaptive Markov Random Fields

This paper introduces a new supervised classification method for hyperspectral images that combines spectral and spatial information. A support vector machine (SVM) classifier, integrated with a subspace projection method to address the problems of mixed pixels and noise, is first used to model the...

Full description

Bibliographic Details
Main Authors: Haoyang Yu, Lianru Gao, Jun Li, Shan Shan Li, Bing Zhang, Jón Atli Benediktsson
Format: Article
Language:English
Published: MDPI AG 2016-04-01
Series:Remote Sensing
Subjects:
hyperspectral image classification
support vector machines (SVMs)
subspace projection method
adaptive Markov random field
Online Access:http://www.mdpi.com/2072-4292/8/4/355

Similar Items

Similar Items