首页> 外文会议>第21届国际摄影测量与遥感大会(ISPRS 2008)论文集 >MATCHING CONJUGATE POINTS BETWEEN MULTI RESOLUTION SATELLITE IMAGES USING GEOMETRIC AND RADIOMETRIC PROPERTIES
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MATCHING CONJUGATE POINTS BETWEEN MULTI RESOLUTION SATELLITE IMAGES USING GEOMETRIC AND RADIOMETRIC PROPERTIES

机译:利用几何和辐射特性匹配多分辨率卫星图像上的共轭点

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Remotely sensed images are the main source for a variety of mapping and change detection applications. Images from different satellites are employed in several of these applications. However, each type of these images has different resolution and orientation. Hence, they need to be co-registered before any meaningful utilization. The first step in the registration process is to find conjugate points between the images. This paper presents a modified approach of Scott and Longuet-Higgins approach to find conjugate points between different remotely sensed images. In such an algorithm, initially, comer points are extracted automatically in two images, and for each pair of points a cost value is computed. The cost of corresponding any two points is computed using image coordinates and pixel intensities. The cost values are then used to fill a cost matrix, and its SVD is used to find correspondent points. The algorithm is tested on three pairs of satellite images with different resolutions and orientations. Result shows that the presented approach succeeded in finding more than 96% of conjugate points between two different satellite images using only the image coordinates. Moreover, result shows that including the image intensities in the matching procedure does not improve the results significantly.
机译:遥感图像是各种映射和更改检测应用程序的主要来源。这些应用中的几种应用了来自不同卫星的图像。但是,这些图像的每种类型都有不同的分辨率和方向。因此,在进行任何有意义的利用之前,需要先共同注册它们。配准过程的第一步是找到图像之间的共轭点。本文提出了一种改进的Scott和Longuet-Higgins方法,可以找到不同遥感图像之间的共轭点。在这种算法中,最初,在两个图像中自动提取角点,并为每对点计算成本值。使用图像坐标和像素强度计算对应任意两个点的成本。然后使用成本值填充成本矩阵,并使用其SVD查找对应点。该算法在三对具有不同分辨率和方向的卫星图像上进行了测试。结果表明,所提出的方法仅使用图像坐标就能成功找到两个不同卫星图像之间超过96%的共轭点。而且,结果表明在匹配过程中包括图像强度并不能显着改善结果。

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