DocumentCode :
3068082
Title :
Target detection on high-resolution SAR image using Part-based CFAR Model
Author :
Chu He ; Yu Zhang ; Xin Su ; Xin Xu ; Ming-sheng Liao
Author_Institution :
Sch. of Electron. Inf., Wuhan Univ., Wuhan, China
fYear :
2013
fDate :
21-26 July 2013
Firstpage :
3570
Lastpage :
3573
Abstract :
This letter proposed a Part-based CFAR Model for object detection of power tower on high-resolution SAR images. Firstly, Part-based Model is used to describe the structure feature of the target, then Compressing Sensing approach is added to reduce the speckle by means of rebuilding background clutter, next, CFAR method is used to extract local shape and scale parameters, at last, Part-based CFAR Model combines these procedures together to form the finally algorithm, not only includes the distribution features, but also considers the structure relationship in the proposed approach. The algorithm is tested on TerraSAR-X data set with the resolution of 1m and 3m. Experiments show that unlike the CFAR method can only gives the high-light points of the targets; Part-based CFAR Model illuminates the target and its local components by plotting the bounding boxes around them.
Keywords :
geophysical image processing; object detection; radar imaging; remote sensing by radar; synthetic aperture radar; CFAR method; TerraSAR-X data set; compressing sensing approach; high-resolution SAR images; object detection; part-based CFAR model; target detection; Abstracts; Adaptation models; Image resolution; Snow; Transforms; CFAR; Compressing Sensing; Part-based Model; SAR; target detection;
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.2013.6723601
Filename :
6723601
Link To Document :
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