Video Cluster Encoding with Block-Based Parameter Translation
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Solution Overview
Problem
Current video compression/decompression systems face challenges in achieving high compression efficiency and video quality, especially when encoding large batches of videos in multiple resolutions and bitrates, which affects processing time and user experience.
Innovation Solution
The system generates block-based coding parameters for a video at a first resolution and bitrate, then translates these parameters into encode controls for encoding at different resolutions and bitrates, allowing for independent decoding and optimizing encoding performance by restricting unnecessary evaluations, such as limiting motion vector searches and transform unit split depths.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If video is encoded in multiple resolutions and bitrates with full evaluation of all coding options, then video quality is improved, but processing time increases significantly
Solution Approach 1:
The system performs a preliminary encode at a first resolution to generate initial block-based coding parameters. These parameters are then translated and used as starting points for subsequent encodes at different resolutions, eliminating the need to perform full evaluations from scratch for each resolution and bitrate combination.
Solution Approach 2:
The system changes encoding parameters by translating block-based coding parameters between different resolutions and bitrates. By adjusting resolution and bitrate parameters systematically, the system achieves multiple encodes with reduced processing time while maintaining quality through controlled parameter transitions.
2Loss of energy
If all coding options are evaluated for each video encode, then compression efficiency is optimized, but device complexity increases
Solution Approach 1:
The encoding process is segmented into distinct stages: a preliminary encode stage that generates base coding parameters, and subsequent translation stages that adapt these parameters for different resolutions and bitrates. This segmentation allows the system to perform comprehensive evaluation once, then reuse results across multiple encoding scenarios.
Solution Approach 2:
The system creates and uses copies of block-based coding parameters across different encoding scenarios. By translating and copying parameters from the preliminary encode to subsequent encodes, the system avoids redundant full evaluations while maintaining compression efficiency through parameter adaptation.
3Manufacturing precision
If motion vector searches and transform unit split depths are fully evaluated, then video quality is improved, but processing time increases
Solution Approach 1:
Motion vector searches and transform unit split depth evaluations are performed once during the preliminary encode at the first resolution. The results are then translated and applied to subsequent encodes at different resolutions, eliminating redundant motion searches and split depth evaluations while maintaining video quality through parameter translation.
Data Source
AI summary
Techniques related to video cluster encoding are discussed. Such techniques include encoding the video at a first resolution and first bitrate, translating block based coding parameters corresponding thereto to block based encode controls for encode of the same video at a second resolution or a second bitrate, and encoding the video at the second resolution and/or bitrate using the encode controls.