GPU Texture Pipeline Interdigitation for Autostereoscopic Displays
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Solution Overview
Problem
The high computational cost of creating interdigitation mapping for lenticular-based autostereoscopic displays makes real-time processing of stereoscopic images inefficient, particularly in applications requiring high frame rates, and existing methods are not optimized for hardware-based implementations.
Innovation Solution
The system leverages graphics processing units (GPUs) to perform interdigitation using a texture pipeline, employing masks and pixel shaders to efficiently map perspective views to subpixels, allowing for real-time processing and storage of interdigitation data to reduce computational load.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If software-based interdigitation mapping is used, then mapping accuracy is achieved, but computational time increases linearly with display resolution
Solution Approach 1:
The patent replaces software-based computational processing with hardware-based GPU processing. The interdigitation mapping computation is transferred from CPU software to GPU hardware, utilizing parallel processing capabilities to dramatically reduce computational time while maintaining mapping accuracy. This substitution of processing architecture resolves the contradiction between accurate mapping and computational speed.
Solution Approach 2:
The patent pre-calculates and stores interdigitation mapping data in texture memory before rendering. By performing the computationally intensive mapping calculation in advance and storing results in optimized data structures, the system avoids repeated computations during real-time rendering, thus reducing computational time while preserving mapping precision.
2Manufacturing precision
If high-resolution displays are used, then image quality improves, but computational overhead for interdigitation increases
Solution Approach 1:
The patent segments the interdigitation computation into independent pixel/fragment processing units that can be executed in parallel on the GPU. By dividing the high-resolution display into individual renderable units and processing them simultaneously through shader programs, the system handles high image quality requirements without proportionally increasing overall computational overhead.
Solution Approach 2:
The patent changes the computational parameters by utilizing GPU-specific data formats (textures, vertex buffers) and processing modes (fragment shaders, vertex shaders) that are optimized for parallel processing. This parameter change in computation methodology allows high-resolution rendering with reduced effective computational overhead compared to traditional software approaches.
3Productivity
If real-time processing is implemented, then frame rate improves, but computational resources are overwhelmed
Solution Approach 1:
The patent substitutes CPU-based software processing with GPU-based hardware processing to achieve real-time frame rates. The GPU's dedicated parallel processing architecture handles the computationally intensive interdigitation mapping and rendering operations, enabling high frame rates without overwhelming system computational resources.
Solution Approach 2:
The patent performs interdigitation mapping calculations and prepares rendering data in advance during CPU processing, then transfers pre-processed data to GPU for final rendering. This preliminary action reduces the real-time computational burden on the GPU, enabling sustained high frame rates without resource exhaustion.
4Ease of manufacture
If existing software methods are used, then implementation simplicity is maintained, but real-time performance is insufficient
Solution Approach 1:
The patent replaces software-based processing with hardware-based GPU processing through shader programs. While this requires learning GPU programming paradigms, it provides optimized real-time performance. The substitution maintains relative implementation simplicity by using standardized OpenGL ES shaders and existing GPU pipelines, achieving both performance and ease of implementation.
Data Source
AI summary
A system and method for interdigitating multiple perspective views in a stereoscopic image viewing system. A lenticular sheet is affixed in intimate juxtaposition with a display area having a defined aspect ratio. The display area includes a plurality of scan lines each having a plurality of pixels, each pixel including subpixels. A map having the same resolution as the display is created to store values corresponding to each subpixel in the display area. Preferably, the map is generated beforehand and stored for later use through a lookup operation. A buffer stores a frame having n views, wherein each of the n views has the same aspect ratio as the display area. A plurality of masks is also created and stored. Each mask corresponds to a unique one of the n views and includes opaque areas and a plurality of transparent windows, each of which corresponds to a selected subpixel location. The n views are then interdigitated while applying the corresponding masks, and a value is assigned to each subpixel using the map.