引用本文: 黄攀, 唐劲松, 钟何平. 干涉合成孔径声呐复图像配准分段曲面拟合法[J]. 武汉大学学报 ( 信息科学版), 2021, 46(8): 1259-1264.
HUANG Pan, TANG Jinsong, ZHONG Heping. Piecewise Surface Fitting Method for Complex Image Registration of Interferometric Synthetic Aperture Sonar[J]. Geomatics and Information Science of Wuhan University, 2021, 46(8): 1259-1264.
 Citation: HUANG Pan, TANG Jinsong, ZHONG Heping. Piecewise Surface Fitting Method for Complex Image Registration of Interferometric Synthetic Aperture Sonar[J]. Geomatics and Information Science of Wuhan University, 2021, 46(8): 1259-1264.

## Piecewise Surface Fitting Method for Complex Image Registration of Interferometric Synthetic Aperture Sonar

• 摘要: 复图像配准是干涉合成孔径声呐（interferometric synthetic aperture sonar, InSAS）信号处理中非常关键的环节，配准质量的好坏直接影响到后续的干涉图生成和数字高程重建。针对大场景的InSAS图像用传统的整体多项式曲面拟合法配准精度低的问题，提出了基于分段曲面拟合的InSAS复图像配准方法。首先，将整个待配准图像沿距离向分成具有重叠区域的若干段; 然后，在每段上利用已选出的同名点进行多项式曲面拟合; 最后，将每段曲面拟合的结果拼接成整体偏移量曲面。以均方根误差、相关系数、残余点数目作为评价标准，利用仿真实验和真实的湖上试验数据处理结果验证了该方法的有效性。

Abstract:
Objectives  Complex image registration is crucial in interferometric synthetic aperture sonar (InSAS) signal processing. The registration quality directly influences the generation of interferogram and the subsequent reconstruction of digital elevation model. The traditional global polynomial surface fitting method has the disadvantage of low accuracy for large scene InSAS images. Therefore, a registration method based on piecewise surface fitting is proposed to overcome the problem.
Methods  Firstly, the whole image is partitioned into several pieces along range direction with partly overlapped. Then, polynomial surface fitting is performed using control points in each piece. Finally, the global offset surface is obtained by merging those local surface fitting results.
Results  Through the simulation and real data experiments, the accuracy of complex image registration using the proposed method is higher than the result of global polynomial surface fitting method.
Conclusions  The evaluation has been carried out with the root mean squared error, correlation coefficient, residue numbers, which indicates the validity of the proposed approach.

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