DSM generation method and device based on unmanned aerial vehicle images

Abstract

The invention provides a DSM generation method and device based on unmanned aerial vehicle images, and the method comprises the steps of obtaining an unmanned aerial vehicle image set, and determining the corresponding camera initial internal parameters according to the label data of the unmanned aerial vehicle images in the unmanned aerial vehicle image set; determining an affine transformation relationship between a reference image and a search image according to the feature points corresponding to homonymous image points in an overlapping region of the reference image and the search image in the unmanned aerial vehicle image set; determining the three-dimensional coordinates of the feature points corresponding to the homonymy image points in the overlapping region of the image of which the overlapping region is greater than a preset threshold value, and generating a DSM sparse point cloud according to the three-dimensional coordinates and the initial internal parameters; and obtaining a DSM dense point cloud according to the sparse point cloud by using a multi-view stereo reconstruction method, and generating a DSM corresponding to the unmanned aerial vehicle image. Therefore, the disordered data set can be effectively utilized to carry out rapid and accurate adjustment calculation to realize the three-dimensional reconstruction of a large scene, and the corresponding DSM is generated.

Description

technical field [0001] Embodiments of the present disclosure generally relate to the technical field of image processing, and more specifically, relate to a method and device for generating a DSM based on drone images. Background technique [0002] At present, there is no method in the industry to use UAV images for DSM generation. In the traditional DSM generation work, traditional measurement methods, laser radar methods, and digital photogrammetry methods are often used to complete. These methods have different problems when generating DSM: [0003] 1. When using traditional measurement methods to generate DSM, a lot of manpower and material resources are required, the data acquisition time is long, the update cycle is long, and it is difficult to obtain DSM results in areas where manual field data collection is difficult. [0004] 2. When using the laser radar method to generate DSM, although the elevation data with high precision can be obtained, there is a lack of gro...

AI Technical Summary

Problems solved by technology

[0003] 1. When using traditional measurement methods to generate DSM, a lot of manpower and material resources are required, the data acquisition time is long, the update cycle is long, and it is difficult to obtain DSM results in areas where manual field data collection is difficult

[0004] 2. When using the laser radar method to generate DSM, although the elevation data with high precision can be obtained, but the ground object information is lacking, only the elevation value can be collected, and the data type is too single

[0006] UAVs can continuously acquire high-precision sequential images with large overlaps, but the acquired images will lose depth information

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