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Morphological Feature Extraction for Automatic Registration of Multispectral Images

机译:用于多光谱图像自动配准的形态特征提取

摘要

The task of image registration can be divided into two major components, i.e., the extraction of control points or features from images, and the search among the extracted features for the matching pairs that represent the same feature in the images to be matched. Manual extraction of control features can be subjective and extremely time consuming, and often results in few usable points. On the other hand, automated feature extraction allows using invariant target features such as edges, corners, and line intersections as relevant landmarks for registration purposes. In this paper, we present an extension of a recently developed morphological approach for automatic extraction of landmark chips and corresponding windows in a fully unsupervised manner for the registration of multispectral images. Once a set of chip-window pairs is obtained, a (hierarchical) robust feature matching procedure, based on a multiresolution overcomplete wavelet decomposition scheme, is used for registration purposes. The proposed method is validated on a pair of remotely sensed scenes acquired by the Advanced Land Imager (ALI) multispectral instrument and the Hyperion hyperspectral instrument aboard NASA's Earth Observing-1 satellite.
机译:图像配准的任务可以分为两个主要部分,即,从图像中提取控制点或特征,以及在所提取的特征中搜索用于表示要匹配的图像中的相同特征的匹配对。手动提取控制特征可能是主观的并且非常耗时,并且经常导致很少的可用点。另一方面,自动特征提取允许将不变的目标特征(如边,角和线相交)用作相关的界标,以进行注册。在本文中,我们提出了一种最新开发的形态学方法的扩展,该方法以完全无监督的方式自动提取地标芯片和相应的窗口,以注册多光谱图像。一旦获得了一组芯片窗口对,就基于多分辨率超完备小波分解方案的(分层)鲁棒特征匹配过程用于注册。该方法在NASA的Earth Observing-1卫星上的Advanced Land Imager(ALI)多光谱仪和Hyperion高光谱仪采集的一对遥感场景上得到了验证。

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