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New Point Matching Algorithm Using Sparse Representation of Image Patch Feature for SAR Image Registration

机译:基于图像补丁特征稀疏表示的SAR图像配准新点匹配算法

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摘要

Image registration is an important preprocessing step in many synthetic aperture radar (SAR) image applications. A key issue in image registration is to reliably establish the correspondences between the feature points extracted from the reference and sensed images. A new point matching algorithm is proposed in this paper to align two SAR images. In the proposed method, by considering image patches as the basic units, a novel local descriptor including the intensity and geometric information is assigned to each feature point, which is more robust to speckle noise. Furthermore, a correspondence establishment scheme is introduced based on the reconstruction errors between feature points calculated by the sparse representation (SR) technique, which is designed for achieving accurate matches. Based on the obtained SR coefficients, a coordinate correction procedure is further proposed for improving the localization accuracy of the obtained correspondences. Both simulated deformed and real SAR images are utilized to evaluate the performance. The experimental results indicate that the proposed method yields a better registration performance in terms of both accuracy and robustness.
机译:在许多合成孔径雷达(SAR)图像应用中,图像配准是重要的预处理步骤。图像配准中的关键问题是可靠地建立从参考图像和感测图像提取的特征点之间的对应关系。提出了一种新的点匹配算法来对准两个SAR图像。在所提出的方法中,通过将图像块视为基本单位,将包括强度和几何信息的新颖的局部描述符分配给每个特征点,其对于斑点噪声更加鲁棒。此外,基于稀疏表示(SR)技术计算出的特征点之间的重构误差,引入了一种对应建立方案,该方案旨在实现精确匹配。基于获得的SR系数,进一步提出了一种坐标校正程序,以提高获得的对应关系的定位精度。仿真的变形图像和实际SAR图像均用于评估性能。实验结果表明,提出的方法在准确性和鲁棒性方面都产生了更好的配准性能。

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