Orthoimage tessellation line network automatic selection method based on building roof vector

Abstract

The invention discloses an orthoimage tessellation line network automatic selection method based on a building roof vector. The method comprises the steps of making the building roof vector combine with a digital elevation model (DEM) to automatically generate a building simple model; utilizing the building simple model to calculate an imaging area of a building on a single-chip DOM; automatically generating a testing area initial Voronoi image tessellation line network using positions of pixel nadir points of all images in a measuring area and conducting simplified processing; using the imaging area of the building on the single-chip DOM to conduct optimized selection on all nodes to obtain a sub-optimal tessellation line network; then conducting optimized selection on all tessellation lines in the sub-optimal tessellation line network to obtain an optimal tessellation line network bypassing the imaging area of the building, of the whole measuring area. The orthoimage tessellation line network automatic selection method based on the building roof vector has obvious advantages that a traditional mode in which single ortho-rectification is firstly conducted, then the single-chip DOM is utilized to conduct selection of the tessellation line network is broken through, and the problems that texture malposition occurs caused when the tessellation line network in the measuring area cannot automatically bypass the imaging area of the building and the automatic selection efficiency is low in an existing method are solved.

Description

technical field [0001] The invention relates to the technical field of aerial orthoimage mosaic, in particular to an automatic selection method of orthoimage mosaic line network based on building roof vectors. Background technique [0002] Digital Orthophoto Map (DOM for short) is a digital remote sensing image using a digital elevation model (Digital Elevation Model for short DEM), after digital differential correction of a single image, then mosaic fusion, and finally cut according to a certain map size digital image data. DOM is one of the important 4D products of digital photogrammetry and remote sensing. It is also an important data source for the production and update of basic geographic information data. Urban construction and other fields. With the development of UAV low-altitude remote sensing system, DOM is also playing an increasingly important role in natural disaster rapid disaster assessment and emergency rescue. [0003] The production of DOM image maps mai...

AI Technical Summary

Problems solved by technology

This type of method is essentially pixel-level, the difference is expressed in a single pixel, and the ground features with geometric differences are not expressed as a whole, so the mosaic line will inevitably pass through areas such as buildings, and the algorithm is very complicated and inefficient; The second type is to bypass buildings by automatically searching auxiliary mosaic lines such as DSM or building mapping data

However, the above methods do not take into account that the projection deformation of the image becomes larger towards the edge of the image.

At the same time, most methods only optimize the selection of the mosaic lines between adjacent images, and do not give the optimal selection scheme of the mosaic line network in the entire survey area.

[0006] The Voronoi diagram mosaic line network automatically generated based on the positional relationship of the sequence images can well select the part with the smallest projected deformation on each image as the effective mosaic area, but it cannot guarantee that the mosaic line bypasses the building

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