CTU Bit Size Limit Management in HEVC Hardware Encoders
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Solution Overview
Problem
High Efficiency Video Coding (HEVC) encoders face challenges in managing bit size limits for Coding Tree Units (CTUs), leading to excessive bit counts and the costly process of re-encoding when limits are exceeded, which disrupts the encoding process and imposes computational burdens.
Innovation Solution
A hardware encoder with a bit estimation block and a CTU bit size limit manager that selects quantization parameters to prevent exceeding bit size limits by estimating bit sizes and adjusting quantization parameters proactively, avoiding re-encoding and ensuring compliance with HEVC specifications.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If the encoder uses a very low quantization parameter (QP) to deliver high fidelity for the first image portion, then the quality is improved, but the bit count may exceed the HEVC specification limits due to high entropy in subsequent portions
Solution Approach 1:
The encoder proactively estimates the bit count for each CTU before actual encoding and selects quantization parameters in advance to ensure the bit count will not exceed specification limits. This preliminary estimation and parameter selection prevents bit count violations without requiring re-encoding operations.
Solution Approach 2:
The encoder implements a feedback mechanism where the estimated bit count from the bit count estimator is fed back to the quantization parameter selector, which adjusts the QP accordingly. This closed-loop control ensures that the selected QP will produce encoded data within the HEVC bit count constraints while maintaining optimal quality.
2Quantity of substance
If the encoder re-encodes CTUs with higher QP when bit count exceeds the limitation, then the bit count constraint is satisfied, but the encoding process is disrupted and computational cost increases significantly
Solution Approach 1:
The encoder performs bit count estimation and quantization parameter selection before the actual encoding process. By determining the appropriate QP in advance based on estimated bit count, the encoder avoids the need for re-encoding operations that would disrupt the encoding process and waste computational resources.
Solution Approach 2:
The bit count estimator and quantization parameter selector work together in an integrated system where the estimator provides information that automatically guides parameter selection. This self-service mechanism eliminates the need for external intervention or iterative re-encoding to satisfy bit count constraints.
3Quantity of substance
If the encoder counts bits during the encoding process to avoid exceeding limits, then compliance with HEVC specification is ensured, but the computational complexity and processing time increase
Solution Approach 1:
The bit count estimator serves as an intermediary component that provides predicted bit count information to the quantization parameter selector. This intermediary estimation mechanism allows the encoder to make informed parameter selections without requiring complex real-time bit counting during the encoding process, thereby reducing computational complexity.
Data Source
AI summary
A hardware encoder has a bit estimation block to compute an estimated bit size for a Coding Tree Unit (CTU). A CTU bit size limit manager selects quantization parameters for use in quantization. The quantization parameters are selected based upon the estimated bit size to insure that the CTU in coded form will not exceed a CTU bit size limit.