Video Encoding Optimization for Quality and Bit Rate Trade-offs
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Solution Overview
Problem
Existing video distribution systems face challenges in accurately assessing and maintaining video quality, leading to poor user experience due to variations in quality levels, which can result in excessive resource usage and transmission issues.
Innovation Solution
A method and system for assessing video quality by determining raw per-instance quality measures, adjusting them based on a target quality, and aggregating these measures to provide an overall quality assessment, while optimizing encoding to achieve the best compromise between quality and resource usage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If video quality is increased above target quality, then quality of experience is improved, but bit rate and bandwidth consumption increase excessively
Solution Approach 1:
The system dynamically changes encoding parameters (quantization parameter, resolution, frame rate) based on the difference between actual and target quality metrics. When quality exceeds target, parameters are adjusted to reduce bit rate while maintaining acceptable quality, resolving the contradiction between quality and resource consumption
Solution Approach 2:
The system implements a feedback loop that continuously monitors video quality metrics and compares them against target quality levels. This feedback mechanism enables real-time adjustment of encoding parameters to prevent excessive quality while optimizing bandwidth usage, directly addressing the contradiction
2Loss of energy
If video quality is decreased below target quality, then bit rate consumption is reduced, but quality of experience deteriorates
Solution Approach 1:
The system adjusts encoding parameters dynamically based on quality feedback. When quality falls below target, parameters are modified to increase quality while managing bit rate consumption, resolving the contradiction between resource efficiency and quality maintenance
3Device complexity
If pre-set target quality is used without dynamic adjustment, then system complexity is reduced, but adaptability to user needs deteriorates
Solution Approach 1:
The system transitions from static pre-set quality levels to dynamic quality adjustment based on real-time feedback and user input. This enables the system to adapt to varying target quality requirements while maintaining manageable complexity through automated control algorithms
Data Source
AI summary
Aspects of the present disclosure relate to the assessment on how well and consistent the quality of a video asset satisfies a given target quality level or a time-varying target quality curve, and the optimization on encoding configuration to achieve the best compromise between satisfying the target quality requirement and saving the bit rate/bandwidth cost. The application scope of the present disclosure is generally in, but not limited to, the field of video coding and distributions, including both live and file-based video encoding, broadcasting and streaming systems. Methods and systems implemented based on the present disclosure may achieve the highest accuracy approaching any given target quality with the smoothest quality variation over time, while maximally reduce bit rate/bandwidth and video distribution cost by optimally determining video encoding configurations and parameters.