True-orthophotomap making method oriented to large-scale production

Abstract

The invention provides a true-orthophotomap making method oriented to large-scale production. The method comprises the following steps of: S1) data source processing: preprocessing the acquired digital surface model and remote sensing image; S2) occlusion detection: detecting the region occluded by buildings; S3) occlusion restoration: restoring the detected occluded region according to the visibility of multiple overlapped images, and obtaining the orthophotomap; S4)image mosaicking: combining multiple neighboring orthophotomaps obtained in the step S3 in a mosaicking manner, toning, and obtaining the true-orthophotomap. The method is efficient, quick, accurate and steady, and has wide adaptive range.

Description

technical field [0001] The invention is oriented to the production of basic image maps, and relates to fields such as surveying and mapping, digital cities and smart cities, and network image map services. Background technique [0002] Traditional orthorectification does not take into account the projection deformation of ground objects such as buildings and trees. On large-scale orthophoto images of cities, the oblique occlusion of buildings is very serious, which affects the effective interpretation and utilization of image information. Since the 1990s, with the rise of urban 3D simulation projects around the world and the increasing demand for the application of large-scale urban maps, the research and production of "true orthophotos" using urban 3D models has gradually begun. However, due to the limitations of data sources and occlusion detection technology, real orthophoto production has been difficult to put into large-scale production. [0003] A central issue in tru...

AI Technical Summary

Problems solved by technology

This kind of method is very inefficient when dealing with a large number of complex vector building models; when dealing with raster data, it is difficult to capture the raster deformation caused by camera distortion and projection imaging, which will lead to wrong judgments on the competition relationship, resulting in a large number of artifacts. Occlusion and Pseudo Visible Noise

In addition, this method cannot deal with the pseudo-visibility problem of targets obscured by tall and narrow walls, which is the so-called "M-Portion" problem. The improved method needs to include the wall into the occlusion detection calculation process, which greatly increases the computational workload and complexity.

The root cause of these problems is that the complex and diverse real world is difficult to represent with a simple three-dimensional volume model, and the Z-Buffer technology based on graphics does not take into account the special situation of photogrammetry

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