Volume XL-7/W4
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-7/W4, 45-50, 2015
https://doi.org/10.5194/isprsarchives-XL-7-W4-45-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-7/W4, 45-50, 2015
https://doi.org/10.5194/isprsarchives-XL-7-W4-45-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.

  26 Jun 2015

26 Jun 2015

Extraction of Peak Feature Based on Synthetic Sinc Model in SAR images

Y. Y. Kong1,2, H. Leung2, S. Yan2, and S. Y. Xing2 Y. Y. Kong et al.
  • 1Nanjing University of Aeronautics and Astronautics, College of information science and technology, 29 YuDao street, Nanjing, 210016 JiangSu, China
  • 2University of Calgary, Department of Electrical and Computer Engineering, 2500 university Drive.N.W., Calgary, T2N 1N4 Alberta, Canada

Keywords: SAR Image, Peak Feature, Point Scatters, Gaussian Mask, Synthetic Sinc Model, Fluctuations Analyze

Abstract. Peak is an important feature in Synthetic Aperture Radar(SAR), which represents essence of scattering centre. There are two general approaches in the literature to extract peak. One way is to extract peak after speckle suppression filtering. Using this method, the extracted feature is in accurate, and the algorithm is more complicated. Another is that detecting the amplitude of the peak directly. In order to have a fast and accurate peak extraction, we proposed using the Sinc peak model algorithm in this paper. It directly extracts peak features from the original SAR image without any noise suppression filtering, which is instead of Gauss mask function. The estimation parameters of peaks use QE theorists. Finally, we can get accuracy three parameters to describe peak features. Analytic fluctuation of parameters is compared with Gauss model peaks using truth SAR images. Experimental demonstrate that the new algorithm is more effective than others for extracting peak features in SAR images.