@inproceedings{20de365cae484a5997a91eb5abdce5f6,
title = "Spatial-spectral classification with local regional filter and Markov random field",
abstract = "This paper presents an improved spatial-spectral classification method combining local average filter (LAF) and Markov Random Field (MRF) model. LAF is used for spatial-spectral feature generation for classification, and MRF is for after-classification context analysis. The proposed method utilizes spatial and information before- A nd after-classification, for a more exquisite incorporation of the spatial information in different levels. Classification is done with the classical support vector machine (SVM) classifier. Experimental results demonstrate the improvement from the proposed LAF-SVM-MRF over the LAF-SVM considering before-classification spatial features and SVM-MRF with after-classification spatial features.",
keywords = "context analysis, feature extraction, hyper-spectral data, local region filter, spatial-spectral classification",
author = "Qiong Ran and Wei Li and Qian Du",
note = "Publisher Copyright: {\textcopyright} 2015 IEEE.; 7th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, WHISPERS 2015 ; Conference date: 02-06-2015 Through 05-06-2015",
year = "2015",
month = jul,
day = "2",
doi = "10.1109/WHISPERS.2015.8075447",
language = "English",
series = "Workshop on Hyperspectral Image and Signal Processing, Evolution in Remote Sensing",
publisher = "IEEE Computer Society",
booktitle = "2015 7th Workshop on Hyperspectral Image and Signal Processing",
address = "United States",
}