Hybrid Lossy-Lossless Digital Signal Encoding
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Solution Overview
Problem
Existing digital signal compression methods face challenges in achieving high compression ratios without significant distortion, particularly when applied to voice and video data, where lossy compression methods introduce quality degradation and lossless methods are inefficient.
Innovation Solution
A method that generates a difference signal between the signal to be encoded and a signal of lower attribute rank, and losslessly encodes this difference signal, allowing for selective reproduction of digital signals at varying sampling frequencies and quality levels by combining layered sampling rates and error correction techniques.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If lossy compression methods are used to achieve high compression ratios (1/10 or less), then the compression ratio is improved, but signal distortion and quality degradation occur
Solution Approach 1:
The patent segments the compression process into two distinct parts: lossy compression for the main signal and lossless compression for the error signal. This segmentation allows each part to be optimized independently - the main signal can be heavily compressed while the error signal preserves exact differences, resolving the contradiction between overall compression ratio and signal quality
Solution Approach 2:
The patent creates a composite compression approach by combining lossy and lossless compression methods. The final compressed data structure integrates both lossy-compressed main signal data and losslessly-compressed error data, forming a hybrid system that achieves both high compression ratios and high signal quality by leveraging the strengths of both methods
2Manufacturing precision
If lossless compression is applied directly to voice and video data, then signal quality is preserved, but the compression ratio is low (20 percent or so)
Solution Approach 1:
The patent extracts the error signal (difference between original and lossily-compressed signal) as a separate component. By taking out this error signal and applying lossless compression specifically to it, the system achieves better overall compression than direct lossless compression while maintaining signal quality through precise error reconstruction
Solution Approach 2:
The patent applies different compression qualities to different parts of the signal processing pipeline: lossy compression is applied to the main signal where some quality loss is acceptable, while lossless compression is applied to the error signal where precision is critical. This local differentiation of compression quality optimizes the overall system performance
3Adaptability or versatility
If layered sampling rates are used to provide flexibility in quality selection, then adaptability is improved, but device complexity increases
Solution Approach 1:
The patent creates a dynamic quality selection system where the decoder can adaptively choose different reproduction qualities by selectively processing different layers of compressed data. The system structure allows flexible quality adjustment without requiring complex re-encoding, as the layered organization enables dynamic quality selection through simple data path choices
Data Source
AI summary
A down sampler 13 down samples a digital signal in the sampling frequency thereof from 96 kHz to 48 kHz on a frame-by-frame basis. The converted signal is compression encoded and output as a main code Im. An up sampler 16 converts a partial signal corresponding to the main code Im to a signal having the original sampling frequency 96 kHz, for example. An error signal between the up sampled signal and an input digital signal is generated. An array converting and encoding unit 18 array converts bits of sample chains of the error signal, thereby outputting an error code Pe. On a decoding side, a high fidelity reproduced signal is obtained based on the main code Im and the error code Pe, or a reproduced signal is obtained based on the main code Im only.