Due to the high similarity of photovoltaic images, the difficulty of registering photovoltaic images increases while the accuracy requirement for registering images is high. This article proposed a guided spatial consensus registration algorithm based on local structural similarity constraint. First, local similarity structural constraints are established based on the characteristics of the neighborhood structure among adjacent matching feature points. Second, outliers are eliminated based on the proposed similarity structural constraints to obtain a high-precision matching feature set among a strictly constrained initial matching feature set. Third, the corresponding geometric parameter of the high-precision matching feature set is used as guided information for the selection of the final inlier set from a weakly constrained initial matching feature set. Finally, the proposed method is validated by photovoltaic images with brightness and geometric differences. The experimental results demonstrate the robustness and efficiency of the proposed algorithm in the application of photovoltaic images.

中文翻译：

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基于引导空间一致性特征匹配的光伏图像配准


由于光伏图像的相似度较高，使得光伏图像配准的难度增大，同时配准图像的精度要求较高。本文提出一种基于局部结构相似性约束的引导空间一致性配准算法。首先，根据相邻匹配特征点之间邻域结构的特点，建立局部相似性结构约束。其次，根据所提出的相似结构约束消除异常值，以获得严格约束的初始匹配特征集中的高精度匹配特征集。第三，高精度匹配特征集的相应几何参数被用作从弱约束初始匹配特征集中选择最终内点集的指导信息。最后，通过具有亮度和几何差异的光伏图像验证了所提出的方法。实验结果证明了该算法在光伏图像应用中的鲁棒性和高效性。