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Automatic registration of visible-band and SAR satellite and aerial remotely sensed images.

机译:自动注册可见波段和SAR卫星以及航空遥感图像。

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Image registration is an essential and difficult task where dealing with remotely sensed images. There exist different registration techniques that work with different data. However, no algorithm is known that can accurately register different type sensor's images consistently. This thesis addresses this problem by investigating the development of a fully automatic registration system for synthetic aperture radar (SAR) and optical remotely sensed images. This novel automatic image registration method is based on the extraction and matching of common features that are visible in the image pairs. The algorithm involves the following five steps: noise removal, edge extraction; edge linking, object extraction, and object matching. The application of the proposed automatic image registration model to SAR and visible-band image pairs shows that accurate ground control points (GCPs) can be identified automatically.
机译:在处理遥感图像时,图像配准是一项必不可少且艰巨的任务。存在用于不同数据的不同注册技术。但是,尚无算法能够始终如一地准确记录不同类型传感器的图像。通过研究合成孔径雷达(SAR)和光学遥感图像的全自动配准系统的开发,本论文解决了这个问题。这种新颖的自动图像配准方法基于图像对中常见特征的提取和匹配。该算法包括以下五个步骤:噪声去除,边缘提取,噪声消除和边缘提取。边缘链接,对象提取和对象匹配。提出的自动图像配准模型在SAR和可见波段图像对上的应用表明,可以自动识别出准确的地面控制点(GCP)。

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