Multipath Matching Pursuit for High-Frequency Ultrasound Denoising
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Solution Overview
Problem
High-frequency ultrasound signals are susceptible to noise, leading to low signal-to-noise ratios and detection precision, which hinders effective detection of microdefects due to weak reflected echoes being drowned out by material and system noise.
Innovation Solution
A method and system using a multipath matching pursuit algorithm to construct a discrete overcomplete dictionary, select a global optimal atom, perform interpolation, and reconstruct the signal in a consecutive atomic library to enhance denoising.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If high-frequency ultrasound is used for detection, then detection precision is improved, but signal-to-noise ratio deteriorates due to weak reflected echoes being drowned out by noise
Solution Approach 1:
The patent segments the ultrasound signal processing into multiple stages: signal acquisition, denoising processing using matching pursuit algorithm, and defect detection. By dividing the processing workflow, the system can apply specialized denoising techniques to enhance the weak defect echoes while maintaining detection precision.
Solution Approach 2:
The patent introduces a matching pursuit algorithm as an intermediary processing step between signal acquisition and defect detection. This algorithm acts as a mediator that separates the weak defect signals from the background noise, enabling reliable detection of microdefects that would otherwise be drowned out by material grain noise and system noise.
2Object-affected harmful factors
If conventional denoising technologies are applied to high-frequency ultrasound signals, then noise reduction is achieved, but signal processing effectiveness deteriorates due to the unique characteristics of high-frequency ultrasound
Solution Approach 1:
The patent changes the processing parameters by using a matching pursuit algorithm specifically designed for high-frequency ultrasound signals. This algorithm adapts to the unique characteristics of high-frequency ultrasound, including its pulse nature, concentrated energy distribution, and high time resolution requirements, thereby achieving effective noise reduction while maintaining signal integrity.
Solution Approach 2:
The patent replaces conventional mechanical or simple filter-based denoising methods with an advanced signal processing algorithm (matching pursuit). This substitution enables more sophisticated noise reduction that accounts for the complex characteristics of high-frequency ultrasound signals, improving both noise reduction capability and signal processing effectiveness.
3Measurement precision
If high-frequency ultrasound with extremely high sampling frequency is used, then signal resolution is improved, but calculation efficiency deteriorates due to large signal dimensions
Solution Approach 1:
The patent applies partial action by using the matching pursuit algorithm to selectively process only the most relevant signal components. Instead of processing the entire high-dimensional signal uniformly, the algorithm identifies and processes the dominant atoms or basis functions that carry the essential information, thereby reducing computational burden while maintaining signal resolution.
Solution Approach 2:
The patent applies local quality by focusing computational resources on the specific regions or time intervals where defect echoes are most likely to occur. The matching pursuit algorithm can adaptively allocate processing power to critical signal segments, improving calculation efficiency without sacrificing overall signal resolution.
Data Source
AI summary
The present invention provides an improved method and system for denoising high-frequency ultrasound based on a multipath matching pursuit algorithm. The method includes: acquiring a high-frequency ultrasound detection signal of a to-be-tested sample; constructing a discrete overcomplete dictionary according to the high-frequency ultrasound detection signal, and training the discrete overcomplete dictionary; reconstructing the high-frequency ultrasound detection signal by using a trained dictionary and using a multipath matching pursuit algorithm, and obtaining a global optimal atom; performing interpolation on the global optimal atom, and constructing a consecutive atomic library; and reconstructing the high-frequency ultrasound detection signal in the consecutive atomic library according to a parameter of the global optimal atom, to complete signal denoising. In the present invention, a signal-to-noise ratio and detection precision of a high-frequency ultrasound signal are improved, so that a reflected signal and a position of a microdefect inside a sample can be observed more effectively.