Pipelined Video Transcoder Memory Buffer CABAC Bottleneck
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Solution Overview
Problem
The high computational complexity of Context-Adaptive Binary Arithmetic Coding (CABAC) in H.264 video coding standards leads to performance bottlenecks, especially for large pictures, making real-time encoding and decoding challenging due to mismatched decoding and de-binarization performance.
Innovation Solution
A pipelined video processing system with cascaded transcoders that preprocess and post-process video streams, using enhanced entropy decoding and encoding with a memory buffer to smooth out performance mismatches between arithmetic and syntax decoding, allowing for improved throughput and efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If Context-Adaptive Binary Arithmetic Coding (CABAC) is used for entropy coding in H.264 video coding, then compression efficiency is improved, but computational complexity increases significantly causing performance bottlenecks
Solution Approach 1:
The patent divides the video processing into multiple independent transcoders operating in parallel, each handling specific portions of the video stream. This segmentation allows the computationally intensive CABAC operations to be distributed across multiple processing units, reducing the computational burden on any single unit while maintaining overall compression efficiency.
Solution Approach 2:
The patent implements preliminary preprocessing of video data before entropy coding, including early decoding and binarization steps. By preparing data in advance and organizing it into structured formats, the system reduces the computational complexity of subsequent CABAC operations, enabling real-time processing while maintaining compression efficiency.
2Loss of information
If CABAC encoding/decoding is performed for large pictures, then compression efficiency is improved, but processing speed decreases making real-time processing difficult
Solution Approach 1:
The patent segments large pictures into multiple smaller processing blocks that can be handled by parallel transcoders. Each transcoder processes a portion of the video stream independently, allowing large pictures to be processed concurrently across multiple units, thereby maintaining both compression efficiency and real-time processing speed.
Solution Approach 2:
The patent introduces a temporal dimension by implementing a pipeline architecture where multiple transcoders operate at different stages of processing simultaneously. This allows the system to process large pictures at high throughput by distributing work across time and processing stages, rather than sequentially, thus achieving real-time performance.
3Adaptability or versatility
If frequent I frames are used to support random access, then accessibility is improved, but bit rate consumption increases significantly
Solution Approach 1:
The patent divides the video stream into multiple independent segments processed by different transcoders, each capable of handling random access requests. This segmentation allows the system to support random access without requiring frequent I-frames throughout the entire stream, as any segment can be independently decoded and accessed, thereby reducing overall bit rate consumption while maintaining accessibility.
Data Source
AI summary
A system (and a method) are disclosed for a video processing system with enhanced entropy coding performance. The system includes an entropy decoder configured to divide decoding of an input video stream into arithmetic decoding and syntax decoding. The entropy decoder includes an arithmetic decoding module, a syntax decoding module, a memory management module and a memory buffer connecting the two decoding modules. The arithmetic decoding module is configured to decode the input video stream into multiple bins of decoded input video stream and the syntax decoding module is configured to decode the bins of arithmetically decoded input videos stream into one or more syntax elements. The memory management module uses the memory buffer to accelerate the coding performances of arithmetic decoding and syntax decoding. The system also includes a corresponding entropy encoder configured to encode a video stream with improved coding performance.