DocumentCode :
226410
Title :
The SAR image segmentation superpixel-based with optimized spatial information
Author :
Xiaolin Tian ; Licheng Jiao ; Long Yi ; Xiaohua Zhang
Author_Institution :
Int. Res. Center for Intell. Perception & Comput., Xidian Univ., Xi´an, China
fYear :
2014
fDate :
6-11 July 2014
Firstpage :
171
Lastpage :
177
Abstract :
In this paper, we propose a method of image segmentation, which is based on superpixel and optimized spatial feature. In this paper, the superpixels are taken into account, which can reduce computational burden, and the result of over-segmentation can also be benefit for segmentation results. The main idea of this paper is based on the conventional fuzzy c-means (FCM). The conventional FCM has a better performance. However, it is sensitive to noise. In order to overcome this shortage, we incorporate spatial information of superpixels into the conventional FCM. In order to obtain the better performance, influential degree of spatial information is applied to the conventional FCM to improve segmentation performance Experimental results show that the proposed method achieves excellent performance.
Keywords :
feature extraction; fuzzy set theory; geophysical image processing; image resolution; image segmentation; pattern clustering; radar imaging; synthetic aperture radar; FCM; SAR image segmentation superpixel; fuzzy c-means; optimized spatial feature; optimized spatial information; synthetic aperture radar images; Classification algorithms; Clustering algorithms; Feature extraction; Image segmentation; Linear programming; Noise; Robustness;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Fuzzy Systems (FUZZ-IEEE), 2014 IEEE International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4799-2073-0
Type :
conf
DOI :
10.1109/FUZZ-IEEE.2014.6891528
Filename :
6891528
Link To Document :
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