A dem-based method for merging areas of oblique photography without image control points in aerial photography

Abstract

The invention discloses a DEM (digital elevation model) based image-control-point-free survey area merging method adopting oblique photography. The method comprises the following steps: step 1, calculating a DEM area range of each aerial photographic survey area on the basis of POS data of a UAV (unmanned aerial vehicle); step 2, constructing a regular grid DEM of each survey area with a point-by-point interpolation method on the basis of the DEM area range of the aerial photographic survey area; step 3, calculating DEM datum plane height of the survey area according to route planning specifications in <Specifications for low-altitude digital aerial photography>, and determining flying height difference critical value of every two adjacent survey areas; step 4, calculating actual flying height difference of every two adjacent survey areas on the basis of the POS data of the UAV; step 5, merging the survey areas on the basis that the actual flying height difference is smaller than the flying height difference critical value to finally obtain a merged set of the aerial photographic survey areas which can be subjected to aerotriangulation together. Compared with the traditional artificial merging method, the method has the advantage that aerial photographic survey area matching accuracy and division efficiency are increased substantially.

Description

technical field [0001] The invention relates to a digital elevation model (Digital Elevation Model, DEM)-based method for merging aerial photography surveying areas of oblique photography without image control points. Background technique [0002] With the development of parallel computing technology and the emergence of aerial triangulation technology based on differential GPS positioning (DGPS), fast and dense matching of massive, disordered and multi-resolution images becomes possible. Among them, the Context Capture (formerly Smart3D) automatic 3D reconstruction software, which is currently at the leading level in the industry, can realize the rapid and automatic production of large-scale real-world 3D models without POS data and control points (GCP). However, in the process of UAV aerial photogrammetry in large-area mountainous areas, due to reasons such as the endurance time of UAVs and terrain fluctuations, it is necessary to divide the photography area into multiple ...

AI Technical Summary

Problems solved by technology

[0005] The traditional manual merging method is to try to combine multiple aerial photography survey areas for aerial triangulation through personal experience, and judge the accuracy of the results. If possible, continue to add aerial photography survey areas until the aerial survey area until the triangulation results cannot be accurately oriented

This traditional manual method relies entirely on the experience of data processing personnel to merge, and its matching accuracy and division efficiency are extremely low

[0006] (2) It cannot be applied to large-area mountainous aerial photography data processing

However, due to the undulating terrain in mountainous areas, the altitude difference between aerial photography areas is often large, and at the same time, it is much more difficult to collect control points in mountainous areas than in towns, which makes the traditional artificial merging method unable to be applied to large-scale aerial photography data processing

[0008] The shortcomings of using the traditional manual merging method in the aerial photographic survey area without image control points have caused great difficulties in the accurate matching, rapid division, and production of real-world 3D models of large-scale mountainous aerial photographic data.

More importantly, since the accuracy of aeronautical triangulation by merging multiple aerial photography survey areas is limited by various factors such as the accuracy of original data, adjustment method, image control point layout method, and geometric strength of the regional network, traditional manual methods are used to conduct aerial triangulation. The efficiency of merging shooting areas is very low, resulting in a waste of manpower and hardware resources

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