GPU Volume Rendering via Shader Iteration
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Solution Overview
Problem
Existing methods for visualizing three-dimensional and higher-dimensional image data sets are computationally intensive and costly, particularly when rendering 3D images into 2D projections for display on a two-dimensional screen, often requiring complex optical property models and extensive computation.
Innovation Solution
The use of graphics processing units (GPUs) with programmable vertex and pixel shaders to efficiently render 3D volume images into 2D images, leveraging iterative functions, gradient computations, and off-screen buffering to enhance performance and image quality, while allowing for standard, off-the-shelf component implementation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If direct volume rendering is used to visualize 3D images, then image quality is improved, but computational complexity and cost increase significantly
Solution Approach 1:
The patent replaces traditional CPU-based volumetric rendering with GPU-based rendering architecture. The GPU's parallel processing capability substitutes the sequential mechanical computation approach, enabling efficient evaluation of optical properties along viewing rays without requiring complex intermediate processing steps, thus reducing computational complexity while maintaining image quality
Solution Approach 2:
The patent changes the computational parameters by utilizing the GPU's native parallel architecture to evaluate multiple viewing rays simultaneously. This parameter change in the computational approach allows direct volume rendering to be performed more efficiently, reducing the computational burden while preserving the quality of the rendered 3D images
2Productivity
If traditional CPU-based rendering is used, then implementation is simpler, but rendering speed is slower
Solution Approach 1:
The patent substitutes the traditional CPU rendering mechanism with a GPU-based rendering system. The GPU's architecture is specifically designed for parallel processing of pixel and vertex operations, which naturally accelerates the rendering pipeline by processing multiple viewing rays and image elements simultaneously, thereby significantly improving rendering speed
Solution Approach 2:
The patent leverages the universal programmability of modern GPUs through shader languages (vertex shaders and pixel shaders). This multi-functionality allows the same GPU hardware to perform various rendering operations including geometric transformations, lighting calculations, and texture mapping, all within a single unified architecture that prioritizes rendering speed
3Measurement precision
If complex optical property models are used for accurate rendering, then image accuracy is improved, but computation time increases
Solution Approach 1:
The patent replaces traditional sequential computation with parallel GPU-based computation. Complex optical property models that evaluate emission, reflection, and scattering along viewing rays are computed simultaneously across thousands of pixels using the GPU's parallel architecture, maintaining rendering accuracy while dramatically reducing computation time
Solution Approach 2:
The patent performs preliminary computations in the vertex shader stage by pre-calculating geometric transformations and positioning sample points along viewing rays. This preliminary action prepares the data in advance for the pixel shader stage, where optical property evaluations are performed efficiently in parallel, thereby reducing overall computation time while maintaining accuracy
Data Source
AI summary
In one aspect, the invention provides improvements in a digital data processor of the type that renders a three-dimensional (3D) volume image data into a two-dimensional (2D) image suitable for display. The improvements include a graphics processing unit (GPU) that comprises a plurality of programmable vertex shaders that are coupled to a plurality of programmable pixel shaders, where one or more of the vertex and pixel shaders are adapted to determine intensities of a plurality of pixels in the 2D image as an iterative function of intensities of sample points in the 3D image through which a plurality viewing rays associated with those pixels are passed. The pixel shaders compute, for each ray, multiple iteration steps of the iterative function prior to computing respective steps for a subsequent ray.