期刊
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
卷 60, 期 -, 页码 -出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TGRS.2021.3133863
关键词
Optical sensors; Optical imaging; Radar polarimetry; Adaptive optics; Remote sensing; Optical distortion; Synthetic aperture radar; Dilated convolution; epipolar-oriented template; image registration; relative correction; synthetic aperture radar (SAR)
类别
资金
- National Natural Science Foundation of China [61901439]
- Key Research Program of Frontier Sciences, Chinese Academy of Sciences [ZDBS-LY-JSC036]
Accurate registration of optical and synthetic aperture radar (SAR) images is crucial for multisensor remote sensing applications. However, the practical implementation of directly matching large and high-resolution optical and SAR images remains underexplored. In this study, a robust two-stage registration algorithm is proposed to reduce positioning errors and optimize the correspondence. The algorithm utilizes a novel template matching method based on dilated convolutional feature (DCF) and epipolar-oriented phase correlation to achieve invariance and capture more overlapping areas. Experimental results demonstrate the effectiveness of the proposed framework.
Accurate optical and synthetic aperture radar (SAR) image registration is crucial to multisensor remote sensing applications. Though several algorithms have been proposed, the practical implementation that directly matches large and high-resolution optical and SAR images remains underexplored by the community. Equipped with the satellite positioning parameters, optical and SAR images can be roughly registered based on geographic coordinates. However, the relative positioning accuracy is still dozens, even hundreds of pixels due to the inaccuracies of sensor parameters and elevation. Consequently, we propose a robust registration algorithm, which consists of two stages, where the horizontal positioning errors can be reduced in the first stage, and then, we fine-tune the correspondences in the second stage. Specifically, we propose a novel template matching method based on the dilated convolutional feature (DCF) and epipolar-oriented phase correlation. DCF is constructed by a depthwise-separable dilated convolution with multichannel gradients, which are generated by the Sobel operator for optical images and a ratio of exponentially weighted averages (ROEWA) operator for SAR images. Due to the large reception field of dilated convolution, DCF can retain invariance even for large relative positioning errors. The epipolar-oriented rectangle template, which stretches along the epipolar line, is then proposed to capture more overlapping areas compared to square templates. Furthermore, the outlier removal is implemented in the coordinate system of optical images to avoid the effect of range compression in SAR images. Inliers are finally used to refine the rational polynomial coefficients (RPCs) based on the bundle adjustment technique. Experimental results on high-resolution optical and SAR image products of various scenarios demonstrate the effectiveness of the proposed registration framework. The relative positioning errors of the refined RPCs can be reduced from hundreds of pixels to the subpixel level.
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