Adaptive Prediction Structures for Video Encoding
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Solution Overview
Problem
Existing video coding techniques face challenges in efficiently encoding high-quality video data due to the large amounts of data required, which burdens communication networks and devices, and struggle to adapt to variations in frame characteristics such as scene changes and content types, affecting encoding performance and rate control.
Innovation Solution
The implementation of adaptive prediction structures that dynamically select and switch between different prediction modes and structures based on frame statistics, such as motion and content type, to optimize encoding performance and rate control by varying the prediction distance and structure size.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If adaptive prediction structures dynamically switch between different prediction modes based on frame characteristics, then encoding performance and rate control are improved, but device complexity increases
Solution Approach 1:
The patent implements dynamic adaptation of prediction structures by switching between different prediction modes (e.g., temporal prediction, spatial prediction, adaptive prediction) based on frame characteristics such as motion activity and content type. The encoder analyzes frame statistics and dynamically selects the most appropriate prediction mode, allowing the system to adapt to varying video conditions and optimize encoding performance for each specific frame rather than using a fixed prediction approach throughout the entire video sequence.
2Quantity of substance
If prediction distance and structure size are varied to match frame characteristics, then rate control is optimized, but the complexity of determining optimal prediction parameters increases
Solution Approach 1:
The patent changes prediction parameters such as prediction distance and structure size based on analyzed frame characteristics. The encoder determines motion activity levels and content types, then adjusts prediction parameters accordingly - using larger prediction distances for low-motion frames and smaller distances for high-motion frames. This parameter adaptation allows the system to optimize the balance between compression efficiency and computational complexity for each frame's specific characteristics.
3Loss of energy
If predictive coding is applied to remove redundant bits, then bit rate is reduced, but encoding complexity increases
Solution Approach 1:
The patent employs self-service prediction mechanisms where the encoder automatically analyzes frame characteristics and selects appropriate prediction modes without requiring complex manual configuration. The system uses built-in analysis of motion vectors and frame statistics to autonomously determine the optimal prediction approach, reducing the need for external intervention while maintaining high compression efficiency. This automated self-service approach balances compression performance with operational simplicity.
Data Source
AI summary
Systems, methods, and computer-readable media are described for providing improved video or image encoding, including adaptive prediction structures for encoding video frames. In some examples, systems, methods, and computer-readable media can include obtaining a sequence of frames; determining, based on frame statistics associated with a first frame in the sequence of frames, a prediction structure for encoding the sequence of frames, the prediction structure defining an order in which frames in the sequence of frames are encoded and a prediction distance representing a maximum distance permitted between referencing frames and reference frames in the sequence of frames, and the frame statistics indicating an amount of motion in the first frame. The systems, methods, and computer-readable media can also include encoding one or more of the sequence of frames based on the prediction structure.