Asymmetrical Rate Control for 3D Video Compression
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Solution Overview
Problem
Conventional video compression methods for 3D video struggle with efficient bit allocation across different picture types and coding layers, leading to suboptimal compression and transmission of 3D video content.
Innovation Solution
The implementation of asymmetrical rate control for 3D video compression using the MPEG-4 Multi-view Video Coding (MVC) standard, where bits are allocated based on picture type (I-picture, P-picture, B-picture) and coding view (base view, enhancement view), with more bits allocated to I-pictures and P-pictures in the base view compared to the enhancement view, and prioritization of lower coding layers over higher ones, while considering the correlation level between views for joint bit-allocation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional video compression methods are used for 3D video, then compression is performed, but bit allocation is inefficient across different picture types and coding layers
Solution Approach 1:
The patent applies local quality by allocating different bitrates to different picture types (I-picture, P-picture, B-picture) and different coding layers (base view, enhancement view) based on their specific requirements. I-pictures receive higher bitrates to maintain reference quality, while B-pictures receive lower bitrates as they are predictive. Base view pictures receive preferential allocation over enhancement view pictures, creating localized quality optimization throughout the video stream.
Solution Approach 2:
The patent changes the bitrate parameter dynamically based on picture type and coding layer. The system adjusts allocation parameters to allocate more bits to I-pictures and base view pictures, and fewer bits to B-pictures and enhancement view pictures. This parameter change approach optimizes the balance between compression efficiency and visual quality by adapting bitrate allocation to local content requirements.
2Manufacturing precision
If more bits are allocated to enhance visual quality, then visual quality improves, but transmission bandwidth increases
Solution Approach 1:
The patent implements local quality by prioritizing bitrate allocation to picture types and coding layers that have the greatest impact on perceived visual quality. I-pictures and base view pictures receive higher bitrates to maintain reference quality and spatial accuracy, while B-pictures and enhancement view pictures receive lower bitrates. This localized quality optimization achieves high visual quality where it matters most while controlling overall bitrate.
Solution Approach 2:
The patent applies asymmetry by creating an unbalanced bitrate allocation scheme where base view pictures receive preferential treatment over enhancement view pictures, and I-pictures receive more bits than P or B pictures. This asymmetric allocation recognizes that not all pictures contribute equally to overall video quality, optimizing the quality-to-bitrate ratio by concentrating bits on the most important pictures.
3Device complexity
If uniform bit allocation is used across all picture types, then allocation is simple, but compression efficiency is suboptimal
Solution Approach 1:
The patent resolves this contradiction by implementing local quality-based allocation that differentiates between picture types and coding layers. The system assigns different target bitrates to I-pictures, P-pictures, and B-pictures, and differentiates between base view and enhancement view pictures. This localized differentiation significantly improves compression efficiency compared to uniform allocation, while the allocation rules remain systematic and manageable.
Solution Approach 2:
The patent changes allocation parameters based on picture type and coding layer to optimize compression efficiency. The system dynamically adjusts target bitrate parameters for different picture types, allocating more bits to I-pictures and base view pictures, and fewer bits to B-pictures and enhancement view pictures. This parameter change approach achieves superior compression efficiency without requiring complex adaptive algorithms.
Data Source
AI summary
A video transmitter compresses an uncompressed 3D video into a base view video and an enhancement view video using MPEG-4 MVC standard. The video transmitter allocates bits to compressed pictures of the uncompressed 3D video based on corresponding picture type. More bits are allocated to I-pictures than P-pictures, and more bits are allocated to P-pictures than B-pictures in a given coding view. More bits are allocated to a compressed picture of the base view video than a same type compressed picture of the enhancement view video. The correlation level between the base view video and the enhancement view video is utilized for bit-allocation in video compression. More bits are allocated to a picture in a lower coding layer than to the same type picture in a higher coding layer in a given coding view. Pictures with the same cording order are identified from different view videos for a joint bit-allocation.