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Image registration algorithm for InSAR large scenes via DFT model

  • role： First author第一作者
  • Affiliation：

    School of Electronic Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China

  • Email：weishunjun@uestc.edu.cn
  • Introduction：韦顺军，1983年生，男，副教授，研究方向为合成孔径雷达成像技术。E-mail：weishunjun@uestc.edu.cn
WEI Shunjun,  
  • Affiliation：

    School of Electronic Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China

TANG Xinxin,  
  • Affiliation：

    School of Electronic Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China

ZHANG Xiaoling

résumé

Image registration is key to high-resolution phase extraction and height inversion for interferometry synthetic aperture radar (InSAR). Recently, the registration method with high accuracy and efficiency has been one of the widely discussed issues in High-Resolution Wide-Swath (HRWS) InSAR applications. Different regions of a large scene will cause the pixel offsets of InSAR images to change dramatically. Traditional algorithms of InSAR image registration are based on maximum coherence require substantial block and interpolation processing, which may suffer from huge computational complexity and low precision. An efficient image registration algorithm for InSAR large scenes via DFT model is proposed in this study. In the scheme, a DFT model of InSAR complex image registration is constructed based on the minimum mean square error criteria. Then, the efficient sub-pixel registration for InSAR complex images is achieved via quadtree block and matrix multiplication DFT registration. Simulation and experimental results are presented to confirm the effectiveness of the algorithm. Results demonstrate that the algorithm can achieve subpixel image registration of InSAR large scenes and has high computational efficiency, usually more than thrice that of traditional FFT-based registration methods.

mots-clés

remote sensing;InSAR;complex image registration;quadtree block;maximum coherence criterion;DFT model

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