Adaptive Bit Budget Allocation for Intra Refresh Video Coding
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Solution Overview
Problem
Existing video coding methods lack effective rate control schemes for Intra refresh, leading to bit rate fluctuations and poor subjective quality due to the different bit requirements of Intra and Inter coding modes, especially in error resilient video coding.
Innovation Solution
A method for adaptively determining a bit budget for video encoding by pre-analyzing pictures to calculate a relative complexity index, allocating bits based on this index, and encoding using Intra or Inter modes within attention areas, ensuring a stable bit allocation across a group of pictures.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If Intra refresh is used for error resilient video coding, then error propagation is suppressed and subjective quality is improved, but bit rate fluctuation occurs and buffer overflow/underflow cannot be prevented
Solution Approach 1:
The patent performs pre-analysis of pictures in a group to calculate complexity indices before actual encoding. This preliminary action determines the bit budget allocation in advance, allowing the system to prepare appropriate quantization parameters ahead of time, thus preventing buffer overflow and underflow while maintaining error resilience through Intra refresh
Solution Approach 2:
The patent dynamically adjusts quantization parameters based on calculated complexity indices and allocated bit budgets. By changing these parameters adaptively according to picture complexity and Intra refresh requirements, the system maintains stable bit rate while preserving error resilience properties
2Reliability
If Intra mode is used for encoding, then error propagation is suppressed, but a large amount of bits is produced causing rate fluctuation
Solution Approach 1:
The patent applies Intra refresh selectively to specific regions (attention areas) rather than entire pictures. By identifying and refreshing only the most important regions that require error resilience, the system suppresses error propagation where needed while minimizing overall bit consumption
Solution Approach 2:
Instead of applying Intra refresh to all pictures or all regions, the patent uses partial action by targeting only attention areas that benefit most from error resilience. This partial application reduces bit consumption while maintaining sufficient error protection
3Reliability
If constant quantization parameters are used for Intra refresh, then error resilience is achieved, but appointed bit rate cannot be obtained and buffer control fails
Solution Approach 1:
The patent transitions from static constant quantization parameters to dynamic adaptive quantization parameters. The system calculates complexity indices and adjusts QP values dynamically based on picture characteristics and allocated bit budgets, enabling both error resilience and proper bit rate control
Solution Approach 2:
The patent implements a feedback mechanism where complexity indices are calculated from pre-analyzed pictures, and this information feeds back into the bit budget allocation and quantization parameter selection process. This closed-loop approach ensures both error resilience and bit rate control are achieved
Data Source
AI summary
When for video coding Intra refresh is used, which inserts Intra coded blocks into previously Inter coded pictures, an efficiently adapted rate control method is required for error resilient video coding. A method for adaptively determining a bit budget for encoding video pictures comprises pre-analyzing each of the pictures of a group of pictures, wherein a relative complexity index is calculated for each picture, allocating bits to the pictures based on their relative complexity index and encoding each of the pictures with the allocated number of bits. The pre-analysis comprises selecting pictures for Intra refresh coding, extracting attention area information from the selected pictures, encoding at least the macroblocks of the attention area using Intra mode, calculating for each picture a complexity index, and calculating from the complexity indices of the pictures of the group a relative complexity index for each picture. Thus, a subjectively better video quality is achieved.