Hybrid CABAC Engine Architecture for Video Encoding
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Solution Overview
Problem
Current CABAC engines face high computational demands and resource costs due to processing large video data, particularly in mode decision tasks, which are not efficiently addressed by existing compression techniques.
Innovation Solution
A hybrid architecture is implemented, utilizing a sequential processor with dedicated hardware to classify and process high-use and low-use syntax elements separately, reducing the processing load by over 90% and minimizing hardware resource usage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If CABAC engine processes all syntax elements sequentially, then compression efficiency is maintained, but computational load and processing time increase significantly
Solution Approach 1:
The patent segments syntax elements into two categories: high-usage elements (motion vectors, coefficients) processed by dedicated hardware logic units, and low-usage elements processed sequentially by the processor. This segmentation reduces the computational burden on the sequential processor while maintaining complete CABAC processing functionality.
Solution Approach 2:
The patent introduces a context address generation module that acts as an intermediary between the processor and logic units. This module generates context addresses for both high-usage and low-usage syntax elements, coordinating the parallel hardware processing with the sequential processing framework and enabling efficient resource utilization.
2Productivity
If dedicated hardware logic units are used for high-usage syntax elements, then processing speed increases, but hardware resource usage and device complexity increase
Solution Approach 1:
The patent applies local quality by providing different processing capabilities to different syntax elements based on their usage frequency. High-usage elements receive dedicated hardware acceleration with optimized logic units, while low-usage elements continue to use the general-purpose sequential processor, avoiding unnecessary hardware resources.
Solution Approach 2:
The patent implements partial hardware acceleration by selecting only the most critical syntax elements (motion vectors and coefficients) for dedicated logic unit processing. This partial action approach provides sufficient processing speed improvement without the excessive hardware resource commitment that would result from accelerating all syntax elements.
3Measurement precision
If mode decision task uses compressed data resource prediction, then encoding accuracy improves, but computational demand on CABAC engine increases
Solution Approach 1:
The patent performs preliminary processing of high-usage syntax elements through dedicated logic units before they reach the sequential CABAC engine. This preliminary action prepares the data in advance, reducing the computational demand on the CABAC engine during the critical mode decision task while maintaining the accuracy benefits of compressed data resource prediction.
Data Source
AI summary
A method for high/low usage is provided. The method receives a macroblock data structure and a syntax element at a digital signal processing engine. Further, the method classifies the syntax element as high use or low use. In addition, the method sends the syntax element from the digital signal processing engine to a logic unit, distinct from the digital processing engine, for binarization if the syntax element is high use.