DocumentCode :
2881613
Title :
Study of SAR Image Texture Feature Extraction Based on GLCM in Guizhou Karst Mountainous Region
Author :
Jia Longhao ; Zhou Zhongfa ; Li Bo
Author_Institution :
State Key Lab. Incubation Base for Karst Mountain Ecology Environ. of Guizhou Province, Guizhou Normal Univ., Guiyang, China
fYear :
2012
fDate :
1-3 June 2012
Firstpage :
1
Lastpage :
4
Abstract :
In the application of remote sensing SAR process in Guizhou karst mountainous region, the fragmented terrain and the complicated crops lead to the unsatisfactory precision, which is caused by using the grey value of SAR image simply in the classification. The original image was processed by the FROST filtering window with 7 × 7. After computing the different window size and direction of GLCM, the different texture characteristic values of GLCM were analyzed. The results show that step size of 1 and moving window with 5 × 5 of GLCM gets the optimum characteristic value. In addition, based on the four GLCM characteristic values of each landuse types, the correlation characteristic is fluctuating and easy to distinguish. To improve the precision of SAR image target recognition ability, as the image texture feature, the correlation characteristic will take part in the classification of the whole study area. But the range of the improvement needs further research.
Keywords :
feature extraction; geophysical image processing; image classification; image recognition; image texture; remote sensing by radar; synthetic aperture radar; terrain mapping; China; FROST filtering window; GLCM characteristic values; Guizhou karst mountainous region; SAR image classification; SAR image target recognition; SAR image texture feature extraction; correlation characteristics; fragmented terrain analysis; image texture feature; optimum characteristic value; remote sensing SAR process; Correlation; Entropy; Feature extraction; Filtering; Image texture; Remote sensing; Synthetic aperture radar;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Remote Sensing, Environment and Transportation Engineering (RSETE), 2012 2nd International Conference on
Conference_Location :
Nanjing
Print_ISBN :
978-1-4673-0872-4
Type :
conf
DOI :
10.1109/RSETE.2012.6260741
Filename :
6260741
Link To Document :
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