Journal of Jilin University(Engineering and Technology Edition) ›› 2018, Vol. 48 ›› Issue (6): 1925-1930.doi: 10.13229/j.cnki.jdxbgxb20171002

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Small feature segmentation method for Spaceborne SAR images

LU Zhi-jun1,2(),ZHONG Chao2,WU Jing-yu2   

  1. 1. Key Laboratory of Radar Imaging and Microwave Photonics Technology Ministry of Education, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China
    2. Shanghai Key Laboratory of Space Intelligent Control Technology,Shanghai 201109,China
  • Received:2017-09-25 Online:2018-11-20 Published:2018-12-11

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Abstract:

The image information of spaceborne synthetic aperture radar is rich and complex, and no information can be used to accurately express all the targets. The images of the same kind are very different, and the images of different kinds have great similarity. The traditional method can not solve the above problems, which leads to the low cutting precision. To solve this problem, a new small feature segmentation method for spaceborne SAR image is proposed. The gray-scale feature of the spaceborne SAR image is extracted, and the texture features are extracted by gray-scale symbiotic matrix. The feature contour model of spaceborne synthetic aperture radar image can be identified by spectral embedded clustering method, and the contour feature is extracted. The SVM is used to segment the small feature of spaceborne SAR image, and the spatial relationship of the over segmented parts is studied by using different small feature information. In the global range, the similar over segmentation parts are processed by iterative growth, and the small feature segmentation is carried out on the spaceborne synthetic aperture radar image. Experimental results show that the proposed method has high accuracy.

Key words: information procession technology, spaceborne synthetic aperture radar, image small feature, accuracy segmentation

CLC Number: 

  • TP391

Fig.1

Spaceborne SAR image and its grayscale texture feature image"

Fig.2

Spaceborne SAR images"

Fig.3

Initial segmentation results"

Fig.4

Comparison of three methods of segmentation results"

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