Huffman Decoding Table Structure for Single-Access Processing
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Solution Overview
Problem
Existing Huffman decoding methods require multiple accesses to a tree structure for decoding Huffman encoded data, leading to inefficient processing and redundant storage.
Innovation Solution
A decoding table data structure is created, allowing single access to decode Huffman encoded data by using symbol-length pairs to reconstruct a decoding table that corresponds to the size of the encoded symbol alphabet, eliminating redundant storage and enabling efficient decoding.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a tree structure is used for Huffman decoding, then the decoding process can be performed, but multiple accesses are required leading to inefficient processing
Solution Approach 1:
The patent creates a decoding table that is a simplified copy of the Huffman tree structure, where each entry directly stores the decoded symbol value. This copying approach eliminates the need for multiple tree traversals by pre-organizing the decoding information in a flat table format that can be accessed in a single operation.
Solution Approach 2:
The decoding table is segmented into multiple entries, each corresponding to a possible bit pattern in the encoded data. Each entry contains pre-computed decoding information, allowing the system to segment the decoding process into discrete, directly-accessible table lookups rather than sequential tree traversals.
2Quantity of substance
If a tree structure is used for Huffman decoding, then decoding can be performed, but redundant storage occurs
Solution Approach 1:
Instead of storing the complete tree structure with all its nodes and pointers, the patent creates a compact decoding table that copies only the essential decoding information. This table stores direct mappings from bit patterns to symbols, eliminating redundant pointer structures and node overhead inherent in tree representations.
Solution Approach 2:
The patent changes the structural parameters of the decoding data structure from a hierarchical tree format to a flat table format. This parameter change transforms the organization from parent-child node relationships to direct key-value mappings, reducing storage requirements while maintaining decoding functionality.
Data Source
AI summary
A method of decoding Huffman-encoded data may comprise receiving a symbol associated with the Huffman encoded data, selecting a target group for the symbol based on a bit length value associated with the symbol, associating the symbol with the target group, associating the symbol with a code, and incrementing a starting code for each of a plurality of groups associated with a starting code that is equal to or greater than the starting code of the target group.