Bypass Sub-Stream Encoding for Low-Latency Entropy Coding
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Entropy encoding and decoding processes, such as arithmetic encoding, can be bottlenecks for processing image, video, and point cloud data due to high computational expense and serializable nature, particularly when dealing with symbols that have even probabilities of occurrence, which do not benefit from compression and require processing resources.
Innovation Solution
A system separates bitstreams into compressible and non-compressible symbol sub-streams, where the non-compressible symbols are bypassed from entropy encoding, allowing for the formation of chunks or packets that can be transmitted or stored independently of fully encoded symbols, reducing latency by allowing partial bitstreams to be processed and transmitted earlier.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of substance
If all symbols are entropy encoded, then compression efficiency is improved, but encoding latency and computational expense increase
Solution Approach 1:
The bitstream is segmented into two separate sub-streams: a compressible symbol sub-stream that undergoes entropy encoding and a non-compressible symbol sub-stream that bypasses the encoder. This segmentation allows the system to apply compression only where beneficial while avoiding unnecessary processing delays for symbols that cannot be compressed, thereby resolving the contradiction between compression efficiency and encoding latency.
Solution Approach 2:
Non-compressible symbols are extracted from the main bitstream and routed through a bypass path that skips the entropy encoding stage entirely. This extraction eliminates the computational expense and time consumption associated with encoding symbols that would not benefit from compression, while the compressible symbols continue to be encoded for optimal compression efficiency.
2Reliability
If full bitstreams are buffered before transmission, then encoding completeness is ensured, but transmission latency increases
Solution Approach 1:
The system performs preliminary actions by separately preparing compressible and non-compressible symbol sub-streams through different processing paths. The bypass sub-stream is ready for immediate transmission without waiting for the completion of entropy encoding, allowing partial bitstreams to be transmitted earlier while maintaining encoding completeness through the separate handling of all symbol types.
3Loss of substance
If entropy encoding is applied to all symbols, then data compression is maximized, but computational resources are wasted on non-compressible symbols
Solution Approach 1:
Different processing qualities are applied to different parts of the bitstream based on their compressibility characteristics. Compressible symbols receive full entropy encoding treatment to maximize compression, while non-compressible symbols receive a simplified bypass treatment that consumes minimal computational resources. This local differentiation optimizes the balance between data compression and computational resource utilization.
Data Source
AI summary
A system comprises an encoder configured to entropy encode a bitstream comprising both compressible and non-compressible symbols. The encoder parses the bitstream into a compressible symbol sub-stream and a non-compressible sub-stream. The non-compressible symbol sub-stream bypass an entropy encoding component of the encoder while the compressible symbol sub-stream is entropy encoded. When a quantity of bytes of entropy encoded symbols and bypass symbols is accumulated a chunk of fixed or known size is formed using the accumulated entropy encoded symbol bytes and the bypass bytes without waiting on the full bitstream to be processed by the encoder. In a complementary manner, a decoder reconstructs the bitstream from the packets or chunks.