Huffman Decoding Priority Analysis for Faster Image Decoding
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional image decoding devices require extensive processing time to detect Huffman codes, particularly due to the need for repeated coincidence detection across 174 Huffman codes, which is inefficient given varying frequencies of occurrence among these codes.
Innovation Solution
The image decoding device incorporates a Huffman decoding unit with a code analysis unit that prioritizes processing variable length code data based on high-frequency Huffman codes, using primary and continuous analysis processing units to recognize zero run and group number information, thereby reducing the number of codes that need to be processed and shortening detection time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If conventional Huffman code detection processes all 174 Huffman codes sequentially, then complete code detection is achieved, but processing time is excessively long
Solution Approach 1:
The patent segments the 174 Huffman codes into multiple groups based on their occurrence frequencies. The segmentation divides the detection task into priority levels, where high-frequency codes are detected first in a first detection stage, and remaining codes are detected in subsequent stages. This segmentation reduces the time for detecting the most common codes while maintaining complete detection accuracy.
Solution Approach 2:
The patent changes the detection parameter by introducing a frequency-based priority system. Instead of treating all Huffman codes equally, the system assigns different detection priorities based on occurrence frequencies. This parameter change allows the decoder to focus computational resources on the most frequently occurring codes first, significantly reducing average detection time.
2Reliability
If all Huffman codes are processed with equal priority, then comprehensive detection is ensured, but processing efficiency is reduced
Solution Approach 1:
The patent performs preliminary action by pre-calculating and storing the occurrence frequencies of all 174 Huffman codes before the actual decoding process. This preliminary frequency analysis enables the system to establish a detection priority order in advance, so that during real-time decoding, the system can immediately proceed with high-frequency codes without performing additional analysis, thus ensuring both accuracy and efficiency.
Solution Approach 2:
The patent substitutes the mechanical sequential processing system with a frequency-based priority scheduling system. Instead of mechanically processing codes in a fixed sequence, the system dynamically prioritizes codes based on their statistical frequencies, replacing rigid mechanical processing with a more intelligent, data-driven approach that maintains reliability while improving productivity.
Data Source
AI summary
An input control unit collectively sends a plurality of pieces of variable length code data. A primary analysis processing unit processes a first piece of variable length code data, recognizes zero run information, group number information, and overhead bit information relating thereto, and outputs them to a frequency conversion unit. A continuous analysis processing unit processes one or more pieces of variable length code data subsequent to the first piece of variable length code data. In the case of variable length code data targeted for a predetermined process, the continuous analysis processing unit recognizes zero run information, group number information, and overhead bit information relating thereto, and output them to the frequency conversion unit. In the case of not the variable length code data targeted for the predetermined process, the continuous analysis processing unit discards this and subsequent pieces of data.