Hybrid Variable Fixed Length Data Compression Encoding
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Solution Overview
Problem
Current data compression techniques face inefficiencies in processing time and circuit size due to variable length coding (VLC) for data with high occurrence probabilities, and fixed length coding (FLC) is not suitable for compressing data with significant content like video and audio signals.
Innovation Solution
A device and method that transforms time-domain data into frequency-domain data and classifies it based on occurrence probability for hybrid encoding, using variable length coding for high probability data and fixed length coding for low probability data, with encoded data stored and decoded efficiently to minimize processing time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of substance
If variable length coding is used for data with high occurrence probability, then compression ratio is improved, but decoding time and circuit complexity increase
Solution Approach 1:
The patent segments the frequency domain data into multiple groups based on occurrence probability. High probability data (e.g., AC coefficients with values 0, 1, -1, 2, -2) are separated from low probability data. Each segment is then encoded using the most appropriate coding method: VLC for high probability data to achieve compression, and FLC for low probability data to enable faster decoding. This segmentation resolves the contradiction by applying different coding strategies to different data segments.
Solution Approach 2:
The patent applies different coding qualities to different parts of the data based on their local characteristics (occurrence probability). Instead of using a uniform coding approach, the system performs bit-by-bit analysis to determine the occurrence probability of each coefficient and applies VLC or FLC locally based on that probability. This local quality approach allows the system to optimize both compression ratio and decoding speed for different data regions.
2Loss of substance
If variable length coding is used for data with high occurrence probability, then compression ratio is improved, but circuit size increases
Solution Approach 1:
The patent segments the frequency domain data into multiple groups based on occurrence probability. High probability data (e.g., AC coefficients with values 0, 1, -1, 2, -2) are separated from low probability data. Each segment is then encoded using the most appropriate coding method: VLC for high probability data to achieve compression, and FLC for low probability data to enable faster decoding. This segmentation resolves the contradiction by applying different coding strategies to different data segments.
Solution Approach 2:
The patent applies different coding qualities to different parts of the data based on their local characteristics (occurrence probability). Instead of using a uniform coding approach, the system performs bit-by-bit analysis to determine the occurrence probability of each coefficient and applies VLC or FLC locally based on that probability. This local quality approach allows the system to optimize both compression ratio and decoding speed for different data regions.
3Loss of time
If fixed length coding is used for all data, then decoding speed is improved, but compression ratio deteriorates
Solution Approach 1:
The patent segments the frequency domain data into multiple groups based on occurrence probability. High probability data (e.g., AC coefficients with values 0, 1, -1, 2, -2) are separated from low probability data. Each segment is then encoded using the most appropriate coding method: VLC for high probability data to achieve compression, and FLC for low probability data to enable faster decoding. This segmentation resolves the contradiction by applying different coding strategies to different data segments.
Solution Approach 2:
The patent applies different coding qualities to different parts of the data based on their local characteristics (occurrence probability). Instead of using a uniform coding approach, the system performs bit-by-bit analysis to determine the occurrence probability of each coefficient and applies VLC or FLC locally based on that probability. This local quality approach allows the system to optimize both compression ratio and decoding speed for different data regions.
Data Source
AI summary
A device for data compression includes a domain transformer unit, a classifying unit, a variable length encoder, a fixed length encoder and a memory unit. The domain transformer unit transforms time-domain data into frequency-domain data. The classifying unit determines an encoding type of the frequency-domain data based on occurrence probability of the frequency-domain data. The variable length encoder encodes first frequency-domain data that are determined to be encoded by variable length coding. The fixed length encoder encodes second frequency-domain data that are determined to be encoded by fixed length coding. The memory unit stores the encoded first and second frequency-domain data by relocating the encoded first and second frequency-domain data such that the encoded first frequency-domain data are placed adjacently and the encoded second frequency-domain data are placed adjacently. Therefore, the time for decoding the corresponding data may be reduced.