Tianjin Tilted Photographic Model CompressedThere were usually the following methods to compress an oblique photography model:
1. ** Noodles decreased **:
- The QEM algorithm could be used to reduce the number of triangular patches by optimization of the position and normal of the triangular patches, thereby reducing the model. Although the simplified model might lose some details, the rendering speed would be faster.
2. ** LOD-simplified **:
- Using different levels of detail (LOD) to simplify the model. High-level details (including all aspects) are magnified by the user or presented from a specific angle, while low-level details are used from a distance or from a different angle. Different levels of grids can be created and stored in OSGB format files. The OSGB format also supports zLib or LZMA-based compression, which can reduce the file size for faster transmission and loading.
3. ** Use specific software to operate **:
- For example, he could use the oblique photography processing software, Ling Yi Zhi Mo, to open the oblique photography model file in the OSGB format, right click on the parent node in the Layer window, and select [export].
- If you want to export to OSGB format: select [OSGB] and click on the advanced option. Set [Maximum Level] and [Image Quality] according to your requirements, and then click [Confirm] to complete the compression.
- If you want to export to 3DTiiles format: select [3Dtiles] and click on the advanced option. Set [Maximum Level],[Image Quality],[Draco Compressed] according to your requirements, and then click [Confirm] to complete the compression.
4. ** Using 3D Factory Software **:
- This was a professional software for lightweight processing of 3D models in the OSGB format. The lightweight compression ratio was high, the model lightweight efficiency was high, and the automatic processing ability was high. Under the premise of ensuring the model quality, it could greatly reduce the size of the model file. The processing speed was fast, and it could also support the lightweight compression of super large models.
5. ** Point cloud compression processing (lightened point cloud data for 3D models in oblique photography)**:
- Strengths:
- Reduce data volume: It can reduce the amount of point cloud data to a fraction or less, reducing storage space and transmission bandwith requirements.
- Speed up data transmission and processing: Reduce data transmission time and cost, speed up data processing and analysis, and improve work efficiency.
- Maintaining data accuracy and quality: Modern compression algorithms can reduce the amount of data while maintaining data accuracy and reliability.
- Usage:
- Data transmission and storage: Reduce transmission time and cost, and reduce storage space requirements.
- 3D Model Visualization: Realizing faster and smoother 3D model display and interaction, improving user experience.
- Terrain analysis and application: In the fields of urban planning, land use, resource management, etc., it can be used to generate high-precision terrain models and perform terrain analysis and decision support.
- Challenge:
- The compression algorithm is complicated: the point cloud data has many scattered points and a complex structure, so it is difficult to develop an effective compression algorithm.
- Data maneuverability: Over-compression will result in loss of data accuracy and quality, affecting subsequent analysis and application.
- hardware and software limitations: Requires a large amount of computing resources, increasing system cost and complexity.
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Shaanxi Tilted Photographic Data Price ListIf relevant urban research was carried out based on a certain business line, such as the restoration of the city's panoramic view by tilting photography, the use of drone aerial photography, and data cleaning, there would be different prices depending on the accuracy. Generally, the highest accuracy of the current tilting photography (including data cleaning) would cost up to 70,000 - 80,000 RMB/square kilometer. However, the specific information of the Shaanxi tilting photography data quote was not found.
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