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Agglomerative clustering-based approach for two-dimensional phase unwrapping.

Miguel Arevalillo Herráez1, Jesús G Boticario, Michael J Lalor

  • 1School of Computing, Mediterranean University of Science and Technology, Edificio Galileo Galilei, Avda. de los Naranjos s/n, Valencia 46022, Spain. miguel@must-es.com

Applied Optics
|March 16, 2005
PubMed
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This study introduces a new two-dimensional phase unwrapping algorithm using clustering and heuristics. The novel method dynamically builds a quality-guided path, reducing errors but increasing computation time.

Area of Science:

  • Image Processing
  • Computational Science

Background:

  • Phase unwrapping is crucial for many imaging techniques.
  • Existing quality-guided algorithms can be susceptible to error propagation.

Purpose of the Study:

  • To present a novel algorithm for two-dimensional phase unwrapping.
  • To improve robustness against noise and phase discontinuities.

Main Methods:

  • Combines agglomerative clustering and heuristics.
  • Dynamically constructs a discontinuous quality-guided path during unwrapping.
  • Introduces a variation to reduce execution time.

Main Results:

  • The algorithm demonstrates satisfactory performance with random noise and phase breaks.

Related Experiment Videos

  • Dynamic path construction reduces error propagation compared to static path methods.
  • A variant significantly reduces execution time with minimal impact on results.

    • Conclusions:

    • The novel algorithm offers a robust approach to 2D phase unwrapping.
    • Dynamic path generation enhances reliability, though with a trade-off in speed.
    • The optimized variant provides a practical balance between accuracy and efficiency.