Slice Adaptive Motion Vector Coding for Scalable Video
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Solution Overview
Problem
Existing scalable video coding schemes face inefficiencies in motion vector coding, particularly in terms of bitrate scalability and decoder compatibility, leading to suboptimal coding efficiency and increased complexity, which hinders widespread adoption.
Innovation Solution
Implementing slice adaptive motion vector coding that allows for selection between scalable and non-scalable coding of motion vectors based on criteria such as bitrate scalability, total bitrate efficiency, and decoder requirements, using a syntax field in the bitstream header to determine whether to use a motion vector or its quotient, enabling better tradeoffs in coding efficiency and complexity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If non-scalable motion vector coding is used, then total bitrate coding efficiency is improved, but base layer quality deteriorates and decoder compatibility is reduced
Solution Approach 1:
The video stream is divided into slices, and motion vector coding mode is selected independently for each slice. This allows different regions to use different coding strategies (scalable or non-scalable), enabling the system to optimize for efficiency in some regions while maintaining compatibility in others, thus resolving the contradiction between total bitrate efficiency and base layer compatibility.
Solution Approach 2:
The motion vector coding mode is made dynamic and adaptive rather than fixed for the entire stream. The encoder can switch between scalable and non-scalable modes based on local content characteristics and decoder capabilities, allowing the system to achieve high efficiency where possible while maintaining compatibility where required.
2Adaptability or versatility
If scalable motion vector coding is used, then decoder compatibility is improved, but total bitrate coding efficiency deteriorates
Solution Approach 1:
By segmenting the video into slices with different coding modes, the system can maintain decoder compatibility in regions using scalable coding while achieving higher efficiency in regions using non-scalable coding, thus resolving the contradiction between compatibility and efficiency.
Solution Approach 2:
Different coding strategies are applied to different local regions (slices) based on their specific requirements. Some slices use scalable coding for compatibility, while others use non-scalable coding for efficiency, allowing each region to have optimized quality appropriate to its needs.
3Productivity
If non-scalable motion vector coding is used for all slices, then coding efficiency is improved, but adaptability to different decoder requirements deteriorates
Solution Approach 1:
The system implements dynamic adaptation by allowing the motion vector coding mode to vary across different slices based on decoder requirements and content characteristics. This dynamic approach enables the system to maintain high coding efficiency overall while adapting to specific decoder capabilities when needed.
Solution Approach 2:
The slicing structure provides a universal framework that can accommodate both scalable and non-scalable coding modes within the same bitstream, making the system universally compatible with different decoder types and requirements while maintaining coding efficiency.
Data Source
AI summary
There are provided spatial scalable video encoder and decoders and corresponding methods for scalable video encoding and decoding. A method for spatial scalable video encoding includes selecting between scalable coding and non-scalable coding of motion vectors on a slice basis.