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New region feature descriptor-based image registration method

机译:基于新的区域特征描述符的图像配准方法

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Successful content-based image registration relies on the accurate identification of corresponding features across images. Geometric and photometric transformations between images may hinder an algorithm's ability to precisely match features. In this work, we propose a novel region descriptor detection and matching algorithm for use with image registration. The detection process utilizes invariant feature points, as well as their spatial relationships and textural characteristics to create a connected graph whose structure represents an invariant region descriptor. With such a framework, feature matching can be accomplished by graph matching with a defined similarity metric. Subsequent image registration steps are outlined that employ the invariant region descriptors. The results provide strong evidence of the region descriptor's effectiveness in applications involving image registration. Several scenarios are presented including the registration of general objects, aerial photography, as well as scenes before and after a disaster.
机译:成功的基于内容的图像配准依赖于跨图像的相应特征的准确识别。图像之间的几何和光度转换可能会妨碍算法精确匹配特征的能力。在这项工作中,我们提出了一种新颖的区域描述符检测和匹配算法,用于图像配准。检测过程利用不变特征点及其空间关系和纹理特征来创建一个连接图,其结构表示不变区域描述符。使用这种框架,可以通过使用定义的相似性度量进行图匹配来实现特征匹配。概述了采用不变区域描述符的后续图像配准步骤。结果为区域描述符在涉及图像配准的应用中的有效性提供了有力的证据。介绍了几种方案,包括普通物体的注册,航空摄影以及灾难前后的场景。

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