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Algorithms for suppressing ultrasonic backscattering from material structure.

L Ericsson1, T Stepinski

  • 1Uppsala University, Signals and Systems, Sweden. lars.ericsson@signal.uu.se

Ultrasonics
|August 6, 2002
PubMed
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This paper presents a MATLAB toolbox with algorithms to reduce grain noise in ultrasonic inspection images. The tools, including split spectrum processing and noncoherent detection, improve inspection accuracy by suppressing clutter.

Area of Science:

  • Materials Science
  • Non-destructive Testing
  • Signal Processing

Background:

  • Ultrasonic inspection is crucial for material analysis.
  • Backscattering in pulse-echo ultrasonic inspection creates clutter, known as grain noise.
  • Grain noise significantly impairs the accuracy of ultrasonic inspection results.

Purpose of the Study:

  • To present a MATLAB toolbox with algorithms for suppressing ultrasonic clutter (grain noise).
  • To provide a user-friendly interface for comparing different noise suppression techniques.
  • To enhance the reliability and accuracy of pulse-echo ultrasonic inspection.

Main Methods:

  • Implementation of several grain noise suppression algorithms, including split spectrum processing (SSP) variations.
  • Inclusion of a noncoherent detection (NCD) based algorithm utilizing explicit statistical models.

Related Experiment Videos

  • Development of a graphical user interface for algorithm comparison within the MATLAB environment.

    • Main Results:

    • The toolbox offers a collection of algorithms for ultrasonic clutter suppression.
    • It includes renowned techniques like split spectrum processing (SSP) and novel approaches like noncoherent detection (NCD).
    • The user-friendly interface facilitates the evaluation and comparison of these noise reduction methods.

    Conclusions:

    • The developed toolbox effectively addresses the challenge of grain noise in ultrasonic imaging.
    • It provides researchers and practitioners with valuable tools for improving non-destructive testing.
    • The availability of comparative algorithms and a graphical interface aids in selecting optimal noise suppression strategies.