Huffman Tree Decompression Using Bit Length Histogram Tables
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Solution Overview
Problem
Existing data compression algorithms, such as Huffman coding, require decompression and rebuilding of the Huffman code tree to decompress encoded data, which can be inefficient and complex, especially in hardware implementations.
Innovation Solution
An integrated circuit is designed with tables and circuitry to efficiently decompress data using a bit length histogram table, generating a cumulative histogram table and symbol lookup table to decode variable length codes in a single pass, facilitating the reconstruction of the Huffman code tree.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional Huffman decoding methods are used, then the Huffman code tree can be decompressed and rebuilt, but the process is inefficient and complex in hardware implementations
Solution Approach 1:
The patent segments the decompression process into distinct stages: generating a cumulative histogram table from bit length information, generating a symbol lookup table using the cumulative histogram, and then using these tables for efficient decoding. This segmentation allows each stage to be independently optimized and implemented in hardware, reducing overall complexity while improving decompression efficiency
Solution Approach 2:
The patent performs preliminary actions by pre-generating the cumulative histogram table and symbol lookup table before the actual decoding process. These tables are constructed from the compressed data's bit length information and then stored for use during decompression. This preliminary preparation eliminates the need for complex runtime tree traversal logic in hardware, significantly simplifying the decoding circuitry while maintaining high productivity
2Speed
If the Huffman code tree is decompressed and rebuilt traditionally, then data can be decoded, but latency is increased and processing speed is reduced
Solution Approach 1:
The patent applies preliminary action by constructing the cumulative histogram table and symbol lookup table in advance during the decompression initialization phase. This allows the actual decoding operation to proceed rapidly by simply looking up symbols in the pre-built tables, dramatically reducing decompression latency and increasing processing speed
Solution Approach 2:
The patent creates a simplified copy of the Huffman tree structure in the form of the symbol lookup table, which contains the essential mapping information needed for decoding. Instead of replicating the full tree structure and traversal logic, the patent uses this tabular copy to achieve fast symbol retrieval, thereby reducing time loss while maintaining decoding accuracy
Data Source
AI summary
To decompress encoded data, a Huffman code tree stored in a data header may need to be decompressed and rebuilt. A bit length histogram table is used in a hardware design to more efficiently decompress the Huffman code tree. The bit length histogram table relates each bit length used by the Canonical Huffman Code (CHC) symbols to a corresponding number of symbols in the encoding that have that bit length. Performing decompression using bit length histogram table allows part of the Huffman tree decompression to be performed in a single pass.