Abstract
Abstract. When adopting the matching method of the least squares image based on object-patch to match tilted images, problems like the low degree of connection points for images with the discontinuity of depth or the discrepancy in elevation or low availability of aerotriangulation points would frequently appear. To address such problems, a tilted-image-matching algorithm based on an adaptive initial object-patch is proposed by this paper. By means of the existing initial values of the interior and exterior orientation elements of the tilted image and the information of object points generated in the matching process, the algorithm takes advantage of the method of multi-patch forward intersection and object variance partition so as to adaptively calculate the elevation of the object-patch and the initial value of the normal vector direction angle. Furthermore, this algorithm aims to solve the problem of difficulties in matching the tilted image with its corresponding points brought about by the low accuracy of the initial value of the tilted image when adopting the matching method of the least squares image based on object-patch to match the tilted image with high discrepancy in elevation. We adopt the algorithm as proposed in this paper and the least squares image matching method in which the initial state of the object-patch is horizontal to the object-patch respectively to conduct the verification process of comparing and matching two groups of tilted images. Finally, the effectiveness of the algorithm as proposed in this paper is verified by the testing results.
Highlights
The accuracy in matching the aerial images is a key step in acquiring the information of spatial position of terrain objects by photogrammetry and in conducting the three-dimensional reconstruction of terrain and terrain objects
The image-based matching has developed from gray-based image matching method to feature-based image matching with higher accuracy and reliability, such as aerial image matching based on feature relaxation method (Jiang Wanshou et al.2003), SIFT feature matching algorithm combined with global information (Jihua, 2009), and multi-view image matching method based on feature point guidance (Ji Song et al 2018), and etc
On the basis of classical multi-Photo Geometrically Constrained Matching (MPGC) (Baltsavias E.P., 1991), domestic scholars have, by introducing the concept of object-patch, eliminated the independent affine deformation among images, established a new least-square image matching model, and proposed a least squares image matching method based on object-patch
Summary
The accuracy in matching the aerial images is a key step in acquiring the information of spatial position of terrain objects by photogrammetry and in conducting the three-dimensional reconstruction of terrain and terrain objects. On the basis of classical multi-Photo Geometrically Constrained Matching (MPGC) (Baltsavias E.P., 1991), domestic scholars have, by introducing the concept of object-patch, eliminated the independent affine deformation among images, established a new least-square image matching model, and proposed a least squares image matching method based on object-patch This method reduces the degree of freedom of MPGC algorithm and generates Digital Surface Model (DSM) at the same time of image matching, for which reason it is called image matching method for generating DSM. When using this method for image matching by the literature (Jiang Wanshou, 2004), the image points on the base image are projected to the level of the initial state, and the approximate coordinates of the object points are obtained on the object elements with the outline elevation.
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