Adaptive Video Coding for Bandwidth and Quality Trade-offs
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Solution Overview
Problem
Current video compression and transport technologies face inefficiencies in bandwidth-limited media and storage, particularly in adapting to the variability of video content and human perception of spatio-temporal activity, leading to suboptimal bit allocation and quality in video streaming.
Innovation Solution
A multi-scale adaptive video coding system that analyzes video data at different scales for adaptive bit allocation, utilizing human visual system models to optimize bit distribution based on visual sensitivity and motion content, and employing advanced motion estimation and quantization techniques to balance bit rate and distortion.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If conventional video compression is used, then bandwidth consumption is reduced, but video quality deteriorates due to suboptimal bit allocation
Solution Approach 1:
The patent applies local quality by allocating bits differently across various regions and components of the video signal based on their visual importance. Specifically, it allocates more bits to visually sensitive regions (such as areas with fine details or high contrast) and fewer bits to less sensitive regions, thereby maintaining overall video quality while reducing total bandwidth consumption.
Solution Approach 2:
The patent implements dynamic bit allocation that adapts to the actual content being encoded. The system analyzes spatio-temporal activity in different regions and dynamically adjusts bit allocation in real-time, allocating more bits to regions with high visual activity or importance and fewer bits to static or less important regions, optimizing the trade-off between quality and bandwidth.
2Manufacturing precision
If adaptive bit allocation based on human visual system is implemented, then video quality is improved, but computational complexity increases
Solution Approach 1:
The patent segments the video signal into multiple regions or macroblocks and applies simplified HVS-based bit allocation to each segment independently. This segmentation allows the complex HVS modeling to be applied in a modular fashion, reducing overall computational complexity while still capturing the essential visual sensitivity variations across different regions of the video frame.
3Productivity
If multi-scale adaptive coding is used, then compression efficiency is enhanced, but system complexity increases
Solution Approach 1:
The patent applies multi-scale adaptive coding by analyzing and encoding video content at multiple spatial scales or resolutions. The system processes the video signal at different levels of detail, allocating bits based on the visual importance detected at each scale, thereby enhancing compression efficiency by capturing both coarse and fine visual information optimally.
Data Source
AI summary
Provided is an enhancement to the Video Encoder component of the MPEG standard to improve both the efficiency and quality of the video presentation at the display device.