Video Substream Encoding for Parallel Decoding Efficiency
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Solution Overview
Problem
Existing video encoding and decoding technologies face challenges in efficiently performing parallel decoding, especially with varying numbers of processing cores, leading to increased storage and transmission costs due to high-resolution, high-quality image demands.
Innovation Solution
The method involves configuring video information into substreams that correspond to LCU rows, allowing for effective parallel decoding by matching the number of substreams with the number of processing cores, enabling efficient parallel processing even with diversified core configurations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If video information is divided into substreams for parallel decoding, then decoding efficiency and productivity are improved, but device complexity and configuration complexity increase
Solution Approach 1:
The patent applies segmentation by dividing the video picture into multiple substreams, where each substream corresponds to a specific row of coding units (LCUs). This allows the video decoding process to be divided into independent parallel tasks that can be processed simultaneously by multiple decoding units or processing cores, thereby improving decoding efficiency and productivity.
Solution Approach 2:
The patent implements dynamics by enabling flexible configuration of the number of substreams based on the number of available processing cores. The system can dynamically adjust the substream division to match the processing capability, allowing efficient parallel decoding while avoiding over-complication when fewer cores are available. This dynamic adaptation resolves the contradiction between maximizing productivity and minimizing device complexity.
2Productivity
If the number of substreams is increased to match processing cores, then parallel decoding effectiveness is improved, but adaptability to diversified core configurations deteriorates
Solution Approach 1:
The patent applies dynamics by implementing a flexible substream configuration mechanism that can adapt to different numbers of processing cores. The system dynamically determines the optimal number of substreams based on the available processing cores, allowing efficient parallel decoding when multiple cores are available while maintaining simplicity and adaptability when fewer cores are present. This resolves the contradiction between maximizing parallel decoding effectiveness and maintaining adaptability to diversified core configurations.
Solution Approach 2:
The patent implements universality by designing a substream division method that can universally apply across different processing core configurations. The same basic mechanism of dividing video into substreams works whether there are 2, 4, 8, or any other number of processing cores, making the system versatile and adaptable to various hardware platforms without requiring separate optimization for each configuration.
3Measurement precision
If high-resolution, high-quality image information is transmitted, then image quality and measurement precision are improved, but storage and transmission costs increase
Solution Approach 1:
The patent applies segmentation by dividing the high-resolution video into multiple substreams that can be processed and transmitted in parallel. This allows the system to handle high-resolution image information more efficiently by breaking down the large data量 into smaller, manageable units that can be processed concurrently, thereby reducing the overall storage and transmission burden while maintaining image quality.
Solution Approach 2:
The patent implements continuity of useful action by enabling continuous parallel processing of multiple substreams simultaneously. Instead of processing high-resolution video sequentially which would be time-consuming and resource-intensive, the system continuously processes multiple substreams in parallel, maintaining high image quality while reducing the total time and resources required for transmission and storage.
Data Source
AI summary
A video encoding method includes a step of encoding substreams which are rows of largest coding units (LCUs) in parallel with each other, and a step of transmitting a bit stream including the encoded substreams, where the number of the substreams may be the same as the number of entry points.