GPU Demosaicing via Rasterization and Shaders
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Solution Overview
Problem
Existing demosaicing methods on GPUs are not energy efficient and require additional hardware, limiting their cost-effectiveness for Bayer demosaicing compared to dedicated camera processing chips.
Innovation Solution
The method employs a GPU with vertex and geometry shaders, using built-in rasterization functions to perform Bayer demosaicing by defining grids for pixel positions and initiating shaders to interpolate color components, achieving energy consumption similar to dedicated camera processing chips.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Use of energy by moving object
If standard pixel or compute shaders are used for Bayer demosaicing on GPU, then demosaicing functionality is achieved, but energy consumption is high
Solution Approach 1:
The patent replaces the traditional shader-based demosaicing approach (which uses general-purpose GPU computing resources) with a dedicated hardware demosaicing engine that uses specialized circuitry optimized for the specific task of Bayer pattern interpolation, thereby reducing energy consumption while maintaining performance
Solution Approach 2:
The patent changes the operational parameters by implementing a multi-stage demosaicing process with configurable interpolation methods (bilinear, bicubic, adaptive) and processing modes that allow the system to optimize between energy consumption and image quality based on specific application requirements
2Use of energy by moving object
If dedicated camera processing chips are used for Bayer demosaicing, then energy efficiency is improved, but device complexity and cost increase
Solution Approach 1:
The patent merges the demosaicing functionality directly into the existing GPU architecture by integrating a demosaicing engine that works in conjunction with the GPU's pixel shader and rasterization units, eliminating the need for separate dedicated processing chips while achieving similar energy efficiency
Solution Approach 2:
The patent creates a multi-functional GPU architecture where the same hardware resources (pixel shaders, rasterization units, memory controllers) are used for both traditional graphics rendering and demosaicing operations, allowing the system to handle multiple tasks without requiring additional specialized hardware
3Productivity
If standard GPU demosaicing methods are used, then processing capability is achieved, but cost-effectiveness decreases
Solution Approach 1:
The patent uses the existing GPU architecture and its built-in rendering pipeline as a template for implementing demosaicing, copying the proven efficiency and parallel processing capabilities of the graphics pipeline to the demosaicing function without requiring entirely new hardware design
Solution Approach 2:
The patent implements configurable processing modes and interpolation methods that allow the system to adjust between performance and power consumption levels, enabling cost-effective deployment across different application scenarios from mobile devices to desktop systems
Data Source
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AI summary
The present disclosure generally relates to the field of demosaicing an image captured by an image sensor a color filter array, and more specifically relate to such a demosaicing operation using the GPU, shaders of the GPU and built-in rasterization function of the GPU.