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MULTI-SENSOR IMAGE REGISTRATION BASED ON GEOMETRIC AFFINE INVARIANT

机译:基于几何仿射不变性的多传感器图像配准

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A new automatic feature-based registration algorithm of multi-sensor images with affine deformation is presented.The gray scale discrepancy between corresponding pixels and complex geometric deformation are two challenges in the problem of multi-sensor image registration,which make the design of robust feature descriptor very difficult.In the proposed method,the intersections of extracted line segments from both images are used as the feature points,due to their good robustness against gray scale discrepancy.In contrast to most existing feature-based methods that describe feature points directly,we first construct a new feature,named feature segment,based on the feature points,and then describe each feature segment with a descriptor.The additional procedure of feature segment construction enables us to introduce an algebraic affine invariant into the design of feature descriptor.By doing these,the proposed algorithm's robustness to both affine deformation and gray scale discrepancy can be guaranteed.In addition,since the calculation of feature descriptors only involves simple algebraic operations,the proposed method has low computational load.Experimental results using real multi-sensor image pairs are presented to show the merits of the proposed method.
机译:提出了一种新的基于特征的仿射变形多传感器图像自动配准算法。对应像素之间的灰度差异和复杂的几何变形是多传感器图像配准问题中的两个挑战,这使得鲁棒特征的设计成为可能。描述器非常困难。在该方法中,从两张图像中提取的线段的交点被用作特征点,因为它们具有良好的鲁棒性,可以抵抗灰度差异。我们首先基于特征点构造一个新的特征,称为特征段,然后用描述符描述每个特征段。特征段构造的附加过程使我们能够将代数仿射不变量引入特征描述符的设计中。这样做,所提算法对仿射变形和灰度差异的鲁棒性可以此外,由于特征描述符的计算仅涉及简单的代数运算,因此该方法的计算量较小。提出了使用真实多传感器图像对的实验结果,以证明该方法的优点。

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