Tile Map Compression via Clustering Data Distribution
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Tile maps require significant network transmission bandwidth during loading and display, especially when multiple client devices request map data, leading to high pressure on network resources.
Innovation Solution
A method for tile map processing that involves obtaining point aggregation data and tile serial number distribution information, determining a sequence number for each map tile, generating an aggregation data distribution graph, and applying compression weights to compress map tiles based on these data, reducing data volume and network load.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If tile maps are loaded and displayed using original drawing data, then complete map information is provided, but network transmission bandwidth pressure increases significantly
Solution Approach 1:
The patent extracts only the essential vector information and index data from complete tile map data, transmitting only what is necessary for map display. This extraction process removes redundant information while preserving the core functional elements needed for map rendering, thereby reducing network bandwidth requirements while maintaining map information completeness.
Solution Approach 2:
The tile map data is segmented into vector information and index information, allowing selective transmission and processing. By dividing the complete map data into discrete, manageable components, the system can transmit only the necessary segments (vector data and indexes) rather than the entire dataset, reducing overall network bandwidth pressure.
2Quantity of substance
If all map tiles are compressed uniformly, then network transmission bandwidth is reduced, but visual quality deteriorates
Solution Approach 1:
The patent applies different compression weights to different map tiles based on their individual characteristics and importance. Rather than uniform compression, each tile receives customized compression treatment - high-importance tiles maintain higher quality with lower compression, while less critical tiles undergo more aggressive compression. This local quality approach reduces overall data volume while preserving visual quality where it matters most.
3Quantity of substance
If compression weight is increased for more aggressive compression, then network bandwidth pressure decreases, but data loss increases
Solution Approach 1:
The patent applies partial compression action by using different compression weights for different tiles rather than maximum compression across all tiles. This partial approach ensures that critical map data maintains higher fidelity with minimal compression, while less critical areas receive more aggressive compression. The result is reduced overall data volume with controlled information loss only in non-critical regions.
Data Source
Figure 1~2
Figure 3~4
Figure 5~6
AI summary
The present disclosure relates to the technical field of maps, and provides a tile map processing method and apparatus, an electronic device and a storage medium. The method comprises: for each level of a tile map, acquiring marker clustering data and tile serial number distribution information of the level; determining the serial number of a map tile where the marker clustering data is located, and generating a clustering data distribution diagram according to the serial number and the tile serial number distribution information, the clustering data distribution diagram representing the distribution of the marker clustering data in the map tile of the level; determining a compression weight of each map tile in the level on the basis of the clustering data distribution diagram; and on the basis of the compression weight, compressing the map tile corresponding to the compression weight to obtain a tile compressed map after tile map compression.