Adaptive Distance Field Compression for GPU Volume Rendering
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Volume rendering techniques, such as direct volume rendering, face challenges with high memory consumption due to the need for efficient acceleration methods, leading to a tradeoff between rendering speed and memory usage, especially in applications where memory is scarce, like graphics processing units (GPUs).
Innovation Solution
Adaptive compression and merging of distance field information with existing data structures to reduce memory footprint, allowing for dynamic use of available space without increasing memory consumption, and selecting compression methods based on available storage and performance requirements during runtime.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If distance field information is stored in a separate data structure optimized for fast lookup, then rendering speed is improved, but memory consumption increases
Solution Approach 1:
The patent merges the distance field information with an existing label volume data structure into a single combined dataset. This integration allows the system to utilize unused memory space within the existing data structure, eliminating the need for separate dedicated memory allocation while maintaining fast lookup capabilities during rendering operations.
Solution Approach 2:
The combined data structure serves multiple functions: it stores both label volume information for structure classification and distance field information for empty space identification. This multi-functional approach allows a single data structure to support both rendering acceleration and memory efficiency without requiring additional specialized storage.
2Quantity of substance
If compression methods are applied to distance field information, then memory footprint is reduced, but rendering complexity increases
Solution Approach 1:
The system dynamically selects compression methods based on available storage space and performance requirements during runtime. This adaptive approach allows the rendering system to adjust the level of compression applied to distance field information, optimizing the balance between memory footprint reduction and rendering performance without requiring manual configuration or fixed compression strategies.
Data Source
Figure 1~2
Figure 3
Figure 4
AI summary
In order to decrease a memory footprint for volume rendering, distance field information is adaptively compressed and merged with an existing data structure having unused memory to form a merged dataset. During rendering, the merged dataset is sampled, and a sampled value is used to identify a look-up table for a corresponding voxel or is decompressed and used to skip empty space.