Parallel Video Encoder Bit Budget Allocation
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Solution Overview
Problem
In parallel video encoding, it is challenging for independent encoder instances to cooperate in allocating bit budgets to blocks within frame portions, leading to inefficient allocation of bits, where complex blocks may receive insufficient data while simpler blocks may be over-allocated, due to lack of knowledge about the complexity of blocks assigned to other encoder instances.
Innovation Solution
The solution involves determining a historical complexity distribution of previous frames to allocate bit budgets between parallel encoder instances, allowing each instance to assign bits based on the complexity measure of its assigned frame portion, ensuring that more bits are allocated to complex blocks without requiring communication between encoder instances.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If independent encoder instances encode frame portions in parallel without communication, then encoding speed is improved, but bit budget allocation accuracy deteriorates
Solution Approach 1:
The system performs preliminary analysis of historical complexity distribution from previous frames before actual encoding. This pre-computed complexity information is then used to guide bit budget allocation during parallel encoding, allowing encoders to make informed decisions without real-time communication while maintaining allocation accuracy
Solution Approach 2:
A central controller acts as an intermediary that collects complexity information from all encoder instances, computes the historical complexity distribution, and distributes bit budget allocations back to each encoder. This mediator enables indirect coordination without requiring direct communication between parallel encoder instances during encoding
2Manufacturing precision
If more bits are allocated to complex blocks, then visual fidelity is improved, but overall bit budget efficiency may deteriorate due to lack of global complexity knowledge
Solution Approach 1:
The system uses feedback from historical encoding data, where the complexity distribution from previous frames is fed back into the bit budget allocation process. This feedback mechanism allows the system to learn from past performance and continuously improve bit allocation efficiency while maintaining high visual fidelity for complex blocks
Solution Approach 2:
The system dynamically adjusts the bit budget allocation parameters based on the computed historical complexity distribution. By changing the allocation parameters according to actual complexity measurements rather than using fixed or uniform allocation, the system achieves both high visual fidelity for complex blocks and overall bit budget efficiency
Data Source
AI summary
A technique for encoding video is provided. The technique includes for a first portion of a first frame that is encoded by a first encoder in parallel with a second portion of the first frame that is encoded by a second encoder, determining a historical complexity distribution; determining a first bit budget for the first portion of the first frame based on the historical complexity distribution; and encoding the first portion of the first frame by the first encoder, based on the first bit budget.


