Multi-Processor Rendering With Low-Resolution Preprocessing
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Solution Overview
Problem
High-resolution image rendering in electronic devices leads to increased power consumption, heat generation, and frame freezing due to excessive computing demands.
Innovation Solution
A rendering method involving a first processor instructing a second processor to render images at a lower resolution initially, followed by reading and generating images at a higher resolution, reducing computational load and optimizing memory access to minimize power consumption and improve rendering smoothness.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If the electronic device renders a high-resolution image, then the image quality is improved, but the power consumption is increased and heat is generated
Solution Approach 1:
The rendering process is divided into two stages: first rendering at a lower resolution to reduce computational load, then applying an image processing algorithm (such as super-resolution or sharpening) to enhance the image quality. This segmentation allows the system to achieve high-quality output without the full computational cost of native high-resolution rendering.
Solution Approach 2:
The patent replaces part of the computational rendering workload with an alternative approach using image processing algorithms. Instead of relying solely on the GPU to render every pixel at full resolution, the system uses post-processing algorithms (such as edge detection, sharpening, or AI-based super-resolution) to enhance the lower-resolution image, thereby substituting some mechanical computing operations with algorithmic image enhancement.
2Manufacturing precision
If the electronic device renders a high-resolution image, then the image quality is improved, but the device generates considerable heat
Solution Approach 1:
The rendering process is divided into two stages: first rendering at a lower resolution to reduce computational load, then applying an image processing algorithm (such as super-resolution or sharpening) to enhance the image quality. This segmentation allows the system to achieve high-quality output without the full computational cost of native high-resolution rendering.
3Manufacturing precision
If the electronic device renders a high-resolution image, then the image quality is improved, but frame freezing occurs during running
Solution Approach 1:
The rendering process is divided into two stages: first rendering at a lower resolution to reduce computational load, then applying an image processing algorithm (such as super-resolution or sharpening) to enhance the image quality. This segmentation allows the system to achieve high-quality output without the full computational cost of native high-resolution rendering.
Solution Approach 2:
The system performs preliminary rendering at a lower resolution before applying image enhancement algorithms. This preliminary action reduces the initial computational burden and allows the enhancement algorithms to work on already-rendered data, improving overall rendering efficiency and reducing frame freezing.
Data Source
AI summary
This application provides a rendering method and an apparatus. A first processor receives a rendering command delivered by an application. The rendering command is used to instruct a second processor to render a first image based on a first resolution. The first processor sends a rendering instruction to a second processor. The rendering instruction is used to instruct the second processor to render the first image. The second processor generates image data of the first image with a second resolution based on the rendering instruction. The second resolution is not greater than the first resolution. The second processor writes the image data of the first image with the second resolution into a first memory. The second processor reads image data of the first image with a third resolution from the first memory. The third resolution is greater than the second resolution.