Adaptive Resolution Transcoding for Video Quality
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Solution Overview
Problem
Conventional video coding systems face challenges in optimizing video quality and computing cost when transcoding videos for hosting services, as they fail to efficiently allocate coding bits across videos with varying content complexity, leading to inconsistent quality and user experience.
Innovation Solution
An adaptive transcoding system that uses a video coding complexity engine to measure encoding complexity, a rate-distortion modeling engine to estimate optimal bitrates and resolutions, and adaptive bitrate and resolution transcoding subsystems to adjust transcoding parameters based on video content, ensuring optimized visual quality and reduced computing costs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If a fixed encoding bitrate is applied to all videos, then the computing cost is reduced and processing is simplified, but the video quality becomes inconsistent and deteriorates for videos with varying content complexity
Solution Approach 1:
The patent applies local quality by assigning different encoding parameters (bitrate, resolution) to different videos based on their individual content complexity characteristics. The system analyzes each video's spatial and temporal complexity metrics and tailors the encoding settings specifically for that video, rather than applying a uniform encoding scheme to all content.
Solution Approach 2:
The patent implements dynamics by making the encoding parameters adaptive and variable rather than fixed. The system dynamically adjusts bitrate and resolution based on real-time analysis of video content complexity, allowing the encoding parameters to change according to the specific characteristics of each video being processed.
2Quantity of substance
If a fixed small resolution is used for transcoding, then the storage requirements and bandwidth requirements are reduced, but the video quality deteriorates for videos with simple content such as slide shows and talking heads
Solution Approach 1:
The patent applies local quality by determining the appropriate resolution for each video based on its content complexity. Videos with simple content (slide shows, talking heads) are assigned higher resolutions to maintain quality, while videos with complex content are assigned lower resolutions. This per-video resolution assignment optimizes both storage efficiency and visual quality.
Solution Approach 2:
The patent implements parameter changes by making the resolution parameter variable rather than fixed. The system changes the resolution parameter based on the measured content complexity of each video, allowing simple videos to be encoded at higher resolutions and complex videos at lower resolutions, thereby optimizing the trade-off between quality and storage.
3Manufacturing precision
If traditional rate control algorithms are used to optimize bit allocation within a single video sequence, then the visual quality of individual videos is improved, but the allocation of coding bits among different videos in the corpus is not optimized
Solution Approach 1:
The patent applies segmentation by dividing the video corpus into groups based on content complexity characteristics. Rather than treating all videos uniformly or optimizing each video in isolation, the system segments videos by complexity level and applies appropriate encoding strategies to each segment, achieving both individual video quality and overall system efficiency.
Solution Approach 2:
The patent implements parameter changes by adjusting encoding parameters (bitrate, resolution) based on the content complexity of each video. The system changes these parameters adaptively to optimize the balance between individual video quality and overall system productivity, allowing simple videos to receive more resources while complex videos receive optimized compression.
Data Source
AI summary
An adaptive resolution transcoding system and method adaptively transcodes a source video with an optimized resolution and visual quality based on the video coding complexity (VCC) of the source video. The transcoding system is configured to receive a source video in its native format, and to obtain the video coding complexity score of the source video from a video coding complexity engine. The transcoding system is further configured to set a resolution adjustment level based on the complexity score. Based on the resolution adjustment level, the transcoding system determines an optimal output resolution for the source video for each video output format supported by the transcoding system. Responsive to a user selection of video output format, the transcoding system determines an optimal output resolution for the source video and encodes the source video with the determined optimal output resolution.