DocumentCode :
3088523
Title :
A non-supervised method for shoreline extraction using high resolution SAR image
Author :
Long Zhao ; Ling Fan ; Chao Wang ; Yixian Tang ; Bo Zhang
Author_Institution :
Sch. of Sci., Beijing Jiaotong Univ., Beijing, China
fYear :
2012
fDate :
16-18 Dec. 2012
Firstpage :
317
Lastpage :
322
Abstract :
This paper presents a non-supervised method for shoreline extraction from high resolution synthetic aperture radar (SAR) image. The proposed technique is based on level set with all the parameters optimized in order to be used with different kinds of SAR data and to find the desired boundary with a minimize number of iterations so as to be fast enough. The preprocessing including Roberts Operator and Histogram adjusting is used to enhance the contrast of the boundary. Then we initial the curve to cover the whole image, and an improved level set method is used to do the segmentation. After that, several post-processing steps are utilized to remove any remaining spurious segments. It´s completely non-supervised and can be applied to different kinds of SAR data. The results confirm that the proposed method can provide a stable and fast solution to the shoreline extraction using SAR data.
Keywords :
feature extraction; geophysical image processing; image resolution; oceanographic techniques; radar imaging; radar resolution; synthetic aperture radar; Roberts operator-and=histogram adjusting; high resolution SAR image; level set method; nonsupervised method; shoreline extraction; synthetic aperture radar; Earth; Image resolution; Image segmentation; SAR; Shoreline extraction; level set; non-supervised;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Vision in Remote Sensing (CVRS), 2012 International Conference on
Conference_Location :
Xiamen
Print_ISBN :
978-1-4673-1272-1
Type :
conf
DOI :
10.1109/CVRS.2012.6421282
Filename :
6421282
Link To Document :
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