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Based on the application in the field of photogrammetry, this paper retrospects the binocular image dense matching method. First, the two categories of local dense image matching and global dense image matching methods are concisely compared, and the advantages, disadvantages, and main challenges of each method are pointed out. Then, the building occlusion problem that is difficult to deal with in dense matching is analyzed. The common building occlusion phenomenon in aerial photography is divided into five types, and the pertinence of the existing occlusion detection and filling algorithms is expounded, which provides technical ideas for solving the bottleneck problem in dense image matching. Finally, the development trend of dense image matching of binocular images is prospected. This paper can help readers fully understand the traditional binocular image dense matching technology, and it will be beneficial to the research of dense image matching based on deep learning. [ABSTRACT FROM AUTHOR]

A graph theory-based mismatching detection method is proposed in this paper. At first, two complete graphs are constructed by the correspondences in left and right images, respectively. Then an induced graph is constructed by using the sum of similarity of the triangles corresponding to each node in complete graphs as the attribute value. Finally, the induced graph is refined by removing the node of which the attribute value is the smallest in the graph. In order to automatically locate multiple mismatching points, the graph theory-based mismatching elimination method is a recursive process. The whole process scheme is as follows, complete graph building, induced graph building, and mismatching point locating. The experimental results demonstrates that the accurate mapping model between matched points is not necessary in our mismatching detection method, while the local simila-rity of triangles is sufficient for locating the mismatching points. In addition, the true positive rate is higher and the false positive rate is lower compared to classical RANSAC (random sample consensus) bundler detection method. [ABSTRACT FROM AUTHOR]

We present the principals for BDS and BDS/GPS real-time kinematic (RTK) positioning. A experiment was conducted on Songshan calibration field using a UAV-based low altitude photograph platform which carried a double frequency GNSS system simultaneously receiving BDS and GPS signals. By comparing the positioning result of GPS, BDS, and the BDS/GPS-combined RTK models, and using these three groups of camera exposure station coordinates to carry out GNSS-supported aerotriangulation. These experiments demonstrate that the performance of GPS, BDS and BDS/GPS-combined RTK positioning model are very close in bundle block adjustment. For all three groups, the overall root mean square error was all lower than±0.17 m for the planimetry and±0.25 m for height, which satisfies the Chinese National specifications of aerial photogrammetric 1:500 mapping in hilly regions. [ABSTRACT FROM AUTHOR]

This paper describes a novel method for special textural aerial image matching based on PCA-SIFT. Images are down sampled and subsequently, PCA-SIFT feature matching is applied. The matched points are used to calculate the homography matrix and the corresponding areas are determined between stereo image pairs. PCA-SIFT is performed again on the corresponding areas to get more matching points, and gross errors are detected. Finally, an improved least square image matching method is implemented to refine the PCA-SIFT matching results. Examples of special textural image matching demonstrate that the proposed match method can achieve subpixel accuracy and works well on images with poor texture and repetitive patterns. This method fully satisfies the requirements for automatic aerotriangulation image measurement. [ABSTRACT FROM AUTHOR]

To resolve the oblique image relative orientation problem, in this paper a novel method for relative orientation is proposed based on a fundamental matrix. Firstly, the fundamental matrix is constructed by direct linear transformation, then the elements of relative orientation are deduced with an optimal matrix. Accuracy factors are analyzed for this model, and finally, to get a more accurate solution deploying a rigorous model for relative orientation to the v-parallax. an iterative method is employed that takes elements derived from the essential matrix as the approximate values of the relative orientation elements. Kxperimental results show that our proposed method is feasible for both traditional aerial images and oblique images, and meets the requirements for stereo-model reconstruction in photogrammetrie operations. [ABSTRACT FROM AUTHOR]