DocumentCode :
3062732
Title :
Compressed texton based sorted visual words co-occurrence matrix for high resolution remote sensing imagery classifcation
Author :
Jing Jin ; Chao Tao ; Huiyun Ma ; Zhengrong Zou
Author_Institution :
Sch. of Geosci. & Inf.-Phys., Central South Univ., Changsha, China
fYear :
2013
fDate :
21-26 July 2013
Firstpage :
2605
Lastpage :
2608
Abstract :
A novel, simple, yet effective texture extraction method for high resolution remote sensing imagery classification based on visual words co-occurrence matrix is proposed in this paper. First, Local texture is represented by compressed texton learned from raw image patch with a sorting scheme and random projection. Then the sorted visual words co-occurrence matrix obtained with dictionary learning and nearest neighbor encoding is used for representing global texture. Finally, the support vector machine is applied for classification. Two imagery from Pavia city of Italy with public ground truth dataset are used in our experiments. The results show that the proposed method is effective and outperforms other existing methods.
Keywords :
data compression; feature extraction; image classification; image coding; image representation; image resolution; image texture; learning (artificial intelligence); matrix algebra; remote sensing; support vector machines; compressed texton; dictionary learning; global texture representation; high resolution remote sensing imagery classification; local texture representation; nearest neighbor encoding; public ground truth dataset; random projection; sorted visual words co-occurrence matrix; sorting scheme; support vector machine; texture extraction method; Dictionaries; Educational institutions; Feature extraction; Image classification; Image coding; Remote sensing; Visualization; classification; co-occurrence matrix; high resolution remote sensing imagery; texton; visual words;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Geoscience and Remote Sensing Symposium (IGARSS), 2013 IEEE International
Conference_Location :
Melbourne, VIC
ISSN :
2153-6996
Print_ISBN :
978-1-4799-1114-1
Type :
conf
DOI :
10.1109/IGARSS.2013.6723356
Filename :
6723356
Link To Document :
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