Compressed Data Codebook Reuse for Similar Block Distributions
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Solution Overview
Problem
Existing data compression techniques using probability-based entropy coding result in duplicate transmission of codebooks with similar probability distributions, leading to bulky data due to the inclusion of entire probability tables or codebooks in compressed data.
Innovation Solution
An electronic device is configured to reuse probability tables or codebooks by including only reference information and changes in the compressed data, using rankings of frequencies to determine when similar blocks can share the same replacement data table, thereby reducing data size by transmitting only necessary information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If probability tables or codebooks are included for each block in compressed data, then decoding accuracy is improved, but data size increases due to duplicate transmission
Solution Approach 1:
The patent merges identical or similar probability tables/codebooks across multiple blocks by using a single shared reference table. When blocks have the same or similar probability distributions, instead of including separate codebooks for each block, the system creates one replacement data table and has subsequent blocks reference it, thereby combining redundant information into a single instance.
Solution Approach 2:
The replacement data table serves multiple functions across different blocks. A single replacement data table can be referenced by multiple blocks that share the same probability distribution characteristics, making it a universal resource that performs the decoding support function for multiple blocks simultaneously, reducing overall data redundancy.
2Quantity of substance
If replacement data tables are reused across blocks with similar probability distributions, then data size is reduced, but device complexity increases due to frequency ranking comparisons
Solution Approach 1:
The system performs preliminary frequency ranking of sub-data before creating replacement data tables. By pre-calculating and storing the frequency rankings of sub-data in each block, the system enables efficient comparison with previously processed blocks to determine whether to reuse existing replacement data tables, avoiding the need for complex real-time analysis during compression.
Solution Approach 2:
Instead of creating entirely new replacement data tables for each block, the system copies references to existing replacement data tables when blocks have identical or similar probability distributions. This copying approach, where subsequent blocks reference previously created tables rather than duplicating their contents, significantly reduces data size while maintaining decoding accuracy.
Data Source
AI summary
According to an embodiment of the present disclosure, an electronic device may comprise a memory and a processor configured to produce compressed data by compressing data including a first block and a second block stored in the memory, wherein the processor may be configured to include a first replacement data table corresponding to first sub-data in the compressed data, the first sub-data included in the first block, and the first replacement data table produced based on, at least, rankings of first frequencies for the first sub-data, and include information for reference to the first replacement data table, corresponding to the second block, when second sub-data included in the second block and rankings of second frequencies for the second sub-data meet a designated condition with respect to the first sub-data included in the first block and the rankings of the first frequencies. Other embodiments are also possible.