Media Encoder Selective Evaluation Skipping for Rate-Distortion Optimization
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Solution Overview
Problem
Current video encoding processes are computationally intensive due to the large number of coding tools and options available, leading to time-consuming and resource-intensive operations despite advancements in hardware.
Innovation Solution
A media encoder selectively skips evaluation stages during encoding by analyzing previous decisions and media content to avoid evaluating coding tools, parameters, or modes that do not improve rate-distortion performance, such as determining threshold unit sizes, evaluating motion vectors, applying quantization methods, and disabling transform skip mode based on usage patterns.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If comprehensive evaluation of all coding tools and options is performed during encoding, then rate-distortion performance is optimized, but computational complexity and encoding time increase significantly
Solution Approach 1:
The encoder performs preliminary analysis of the current block characteristics (e.g., transform coefficients, prediction residuals) before evaluating coding tools. Based on this preliminary assessment, the encoder pre-determines which coding tools are likely to be beneficial and which can be skipped, thereby reducing the evaluation scope without significantly compromising rate-distortion performance
Solution Approach 2:
Instead of evaluating all possible coding tools exhaustively, the encoder selectively evaluates only a subset of coding tools that are most relevant to the current block characteristics. This partial evaluation approach achieves acceptable rate-distortion performance while significantly reducing computational complexity
2Measurement precision
If comprehensive evaluation of all coding tools and options is performed during encoding, then rate-distortion performance is optimized, but encoding speed decreases
Solution Approach 1:
The encoder performs preliminary analysis of block characteristics before encoding to identify which coding tools warrant evaluation. This preliminary step enables the encoder to skip unnecessary tool evaluations during the main encoding process, thereby maintaining rate-distortion performance while significantly improving encoding speed
Solution Approach 2:
The encoder selectively skips evaluation of coding tools that are unlikely to improve rate-distortion performance based on preliminary block analysis. By rushing through or skipping these unnecessary evaluations, the encoder maintains acceptable performance while achieving faster encoding speeds
3Measurement precision
If all candidate unit sizes are evaluated during encoding, then rate-distortion performance is optimized, but computational complexity increases
Solution Approach 1:
The encoder adapts the unit size evaluation strategy to local block characteristics. For example, for blocks with certain properties (e.g., smooth regions, high-frequency content), the encoder limits evaluation to specific unit size ranges that are most likely to be optimal, rather than evaluating all possible unit sizes uniformly across all blocks
Solution Approach 2:
Instead of evaluating all candidate unit sizes for every block, the encoder performs partial evaluation by considering only a subset of unit sizes that are most relevant to the current block characteristics, thereby reducing computational complexity while maintaining acceptable rate-distortion performance
4Measurement precision
If all candidate motion vectors are evaluated for contextual motion mode, then rate-distortion performance is optimized, but encoding time increases
Solution Approach 1:
The encoder performs preliminary analysis of motion characteristics and block properties before evaluating candidate motion vectors. Based on this preliminary assessment, the encoder identifies and evaluates only the most promising candidate motion vectors, skipping evaluation of vectors that are unlikely to improve rate-distortion performance, thereby reducing encoding time while maintaining performance
Data Source
AI summary
Various innovations in media encoding are presented herein. In particular, the innovations can reduce the computational complexity of encoding by selectively skipping certain evaluation stages during encoding. For example, based on analysis of decisions made earlier in encoding or based on analysis of media to be encoded, an encoder can selectively skip evaluation of certain coding tools (such as residual coding or rate-distortion-optimized quantization), skip evaluation of certain values for parameters or settings (such as candidate unit sizes or transform sizes, or candidate partition patterns for motion compensation), and/or skip evaluation of certain coding modes (such as frequency transform skip mode) that are not expected to improve rate-distortion performance during encoding.