Reversible Audio Watermarking via Adaptive Quantizer Curves
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Solution Overview
Problem
Digital audio signal watermarking techniques suffer from audio quality degradation with each embedding-and-removal step, and existing reversible methods lack time-variable distortion constraints.
Innovation Solution
The method employs specific quantiser curves in both time and transform domains for embedding watermarks, ensuring reversibility and inaudible signal modifications by controlling the difference between input and output values based on psycho-acoustic masking levels, using a psycho-acoustic masking level calculator and embedder to adjust quantiser curves dynamically.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If conventional QIM watermarking is used, then data rate and capacity are improved, but audio quality degrades with each embedding-removal step
Solution Approach 1:
The patent applies dynamics by making the quantizer curves adaptive and time-variable rather than static. The quantizer characteristics are dynamically adjusted based on the input signal properties and watermark message, allowing the system to optimize between capacity and audio quality preservation across multiple embedding-removal cycles
Solution Approach 2:
The patent changes parameters by using different quantizer curves (with varying step sizes and characteristics) for different watermark messages and signal conditions. This parameter variation allows the system to maintain high data rate while controlling the magnitude of signal modifications to preserve audio quality
2Reliability
If reversible watermarking is used, then audio quality is preserved, but time-variable distortion constraints are not addressed
Solution Approach 1:
The patent introduces time-variable distortion control by dynamically adjusting quantizer characteristics based on local signal properties. The system adapts the quantization step size and curve shape according to the instantaneous signal conditions, providing both reversibility and appropriate distortion control where needed
Solution Approach 2:
The patent applies local quality by using different quantizer characteristics for different parts of the signal and different watermark messages. Each quantizer curve is tailored to local signal conditions and the specific watermark being embedded, providing optimized performance for each local context while maintaining overall reversibility
3Device complexity
If fixed quantizer curves are used, then processing complexity is reduced, but watermark capacity and robustness are limited
Solution Approach 1:
The patent uses dynamics to adjust quantizer characteristics based on the watermark message and signal conditions. By making the quantizer selection and parameters dynamic rather than fixed, the system achieves higher watermark capacity and robustness without requiring prohibitively complex processing
Data Source
AI summary
With quantization index modulation QIM it is possible to achieve a very high data rate, and the capacity of the watermark transmission is mostly independent of the characteristics of the original audio signal, but the audio quality suffers from degradation with each watermark embedding-and-removal step. In order to avoid degradation of the audio quality, the inventive audio signal watermarking uses specific quantizer curves in time domain and in particular in frequency domain for embedding the watermark message into the audio signal, whereby the processing is almost perfectly reversible. Furthermore, it has embedded a power constraint in order to guarantee that the modifications of the audio signal due to the watermark embedding are inaudible.