SAR Segmentation and Recognition Based SCM

Author

Liping Hu ; Xiaoyu Xing

Author_Institution

Sci. & Technol. on Electromagn. Scattering Lab., Beijing, China

fYear

2013

fDate

20-23 Aug. 2013

Firstpage

1533

Lastpage

1537

Abstract

A sub aperture cross-correlation magnitude (SCM) algorithm is presented to improve the contrast between targets of our interest and clutters in synthetic aperture radar (SAR) images. Firstly, the SCM processing is applied to the original image. Secondly, the target region is segmented from the SCM image. Thirdly, the feature vector is extracted from the segmented target contour based on the polar mapping (PM). Finally, the correlation coefficient is used to compute the feature vectors of two contours. Experiments on moving and stationary target recognition (MSTAR) data indicate the effectiveness of the target segmentation and recognition with the SCM processing.

Keywords

feature extraction; image recognition; image segmentation; radar clutter; radar target recognition; synthetic aperture radar; SAR recognition based SCM; SAR segmentation based SCM; SCM processing; clutters; correlation coefficient; feature vector; moving-stationary target recognition; polar mapping; segmented target contour; subaperture cross-correlation magnitude algorithm; synthetic aperture radar images; target recognition; target segmentation; Azimuth; Clutter; Image recognition; Image segmentation; Synthetic aperture radar; Target recognition; Tin; SAR; SCM processing; polar mapping; target segmentation;

fLanguage

English

Publisher

ieee

Conference_Titel

Green Computing and Communications (GreenCom), 2013 IEEE and Internet of Things (iThings/CPSCom), IEEE International Conference on and IEEE Cyber, Physical and Social Computing

Conference_Location

Beijing

Type

conf

DOI

10.1109/GreenCom-iThings-CPSCom.2013.272

Filename

6682284