3D Geospatial Mapping Using Shadow Removal and LOD Segmentation
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Solution Overview
Problem
Current 3D geospatial mapping technologies face challenges in accurately generating high-quality digital surface models from 2D satellite imagery, particularly in urban areas due to issues like large shadow areas, occlusions, and lower accuracy in stereo matching, which affects the quality of road and building models.
Innovation Solution
A method involving preprocessing of satellite imagery to generate point clouds, removing atmospheric clouds and shadows, and creating digital surface and elevation models, followed by layering road networks and computing building geometry, with texturing and multiple levels of detail, to produce accurate 3D geographical information systems maps.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional stereo matching methods are used on 2D satellite imagery, then processing speed is maintained, but mapping accuracy deteriorates due to shadow areas and occlusions
Solution Approach 1:
The patent segments the 3D mapping process into distinct levels of detail (LOD0, LOD1, LOD2, LOD3), where each level processes different levels of geometric detail and complexity. This segmentation allows the system to achieve high accuracy where needed while maintaining processing efficiency for broader areas, resolving the contradiction between mapping accuracy and processing complexity.
Solution Approach 2:
The patent applies preliminary shadow removal and preprocessing to satellite imagery before performing stereo matching. By removing shadows and occlusions in advance, the system improves mapping accuracy without requiring overly complex real-time processing during the main mapping operation.
2Manufacturing precision
If detailed 3D models are generated for all areas, then mapping detail quality improves, but processing time and computational resources increase
Solution Approach 1:
The patent implements local quality by applying different levels of detail (LOD) to different geographic areas based on their importance and characteristics. Critical areas like urban centers receive high-detail processing (LOD2, LOD3), while less critical areas use lower-detail processing (LOD0, LOD1). This resolves the contradiction by maintaining high model detail quality where needed while reducing overall processing time through selective detail levels.
Solution Approach 2:
The patent applies partial action by selectively processing only certain areas at high detail levels rather than uniformly processing entire regions. This allows the system to achieve high model detail quality for important areas while avoiding the excessive processing time that would result from applying the same level of detail everywhere.
3Measurement precision
If shadow removal and preprocessing are applied, then stereo matching accuracy improves, but processing complexity increases
Solution Approach 1:
The patent performs shadow removal and preprocessing as preliminary steps before stereo matching. By addressing shadow and occlusion issues in advance, the system improves stereo matching accuracy without requiring complex real-time processing during the main mapping operation, effectively resolving the contradiction between accuracy improvement and processing complexity.
Data Source
AI summary
Efficient 3D geospatial mapping is disclosed. A 3D geospatial map of an area of interest is generated from 2D satellite imagery. The 2D imagery is preprocessed to generate a point cloud of the area of interest. The point cloud is optimized by removing atmospheric clouds and shadows. A 3D geographical information system (GIS) map with multiple levels of details (LOD) is generated.