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首页> 外文期刊>Geoscience and Remote Sensing, IEEE Transactions on >Automatic Optical-to-SAR Image Registration by Iterative Line Extraction and Voronoi Integrated Spectral Point Matching
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Automatic Optical-to-SAR Image Registration by Iterative Line Extraction and Voronoi Integrated Spectral Point Matching

机译:迭代线提取和Voronoi集成光谱点匹配自动对SAR图像进行光学对SAR配准

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摘要

Automatic optical-to-SAR image registration is considered as a challenging problem because of the inconsistency of radiometric and geometric properties. Feature-based methods have proven to be effective; however, common features are difficult to extract and match, and the robustness of those methods strongly depends on feature extraction results. In this paper, a new method based on iterative line extraction and Voronoi integrated spectral point matching is developed. The core idea consists of three aspects: 1) An iterative procedure that combines line segment extraction and line intersections matching is proposed to avoid registration failure caused by poor feature extraction. 2) A multilevel strategy of coarse-to-fine registration is presented. The coarse registration aims to preserve main linear structures while reducing data redundancy, thus providing robust feature matching results for fine registration. 3) Voronoi diagram is introduced into spectral point matching to further enhance the matching accuracy between two sets of line intersection. Experimental results show that the proposed method improves the matching performance. Compared with previous methods, the proposed algorithm can effectively and robustly generate sufficient reliable point pairs and provide accurate registration.
机译:由于辐射度和几何特性的不一致,自动光学到SAR图像配准被认为是一个具有挑战性的问题。基于特征的方法已被证明是有效的。但是,常见特征很难提取和匹配,并且这些方法的鲁棒性很大程度上取决于特征提取结果。本文提出了一种基于迭代线提取和Voronoi积分谱点匹配的新方法。核心思想包括三个方面:1)提出了一种结合了线段提取和线交叉点匹配的迭代过程,以避免由于不良的特征提取而导致配准失败。 2)提出了从粗到精配准的多级策略。粗注册旨在保留主要的线性结构,同时减少数据冗余,从而为精注册提供可靠的特征匹配结果。 3)将Voronoi图引入到光谱点匹配中,以进一步提高两组线交叉点之间的匹配精度。实验结果表明,该方法提高了匹配性能。与以前的方法相比,该算法可以有效,鲁棒地生成足够的可靠点对并提供准确的配准。

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