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Morphological image processing techniques in thermographic imaging

M A Schulze1, J A Pearce

  • 1Biomedical Engineering Program, University of Texas, Austin 78712.

Biomedical Sciences Instrumentation
|January 1, 1993
PubMed
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This study introduces the LOCO filter, a novel morphological technique for image processing. It effectively suppresses noise and preserves image shapes without introducing bias, crucial for accurate thermographic imaging.

Area of Science:

  • Image Processing
  • Mathematical Morphology
  • Thermographic Imaging

Background:

  • Morphological filters offer shape sensitivity and noise suppression in image processing.
  • Standard morphological operators can introduce statistical and deterministic bias to images.
  • Complementary operators can be averaged to mitigate bias, leading to filters like midrange, pseudomedian, and LOCO.

Purpose of the Study:

  • To develop a bias-free image processing technique for thermographic imaging.
  • To introduce the LOCO filter, combining morphological shape control with noise suppression.
  • To evaluate the impact of structuring element shapes on thermographic images.

Main Methods:

  • Utilized mathematical morphology and set algebra for image filtering.

Related Experiment Videos

  • Developed and applied complementary operator averaging to create the LOCO filter.
  • Tested the LOCO filter on thermographic images of laser-irradiated and electrosurgery-heated tissue.

    • Main Results:

    • The LOCO filter effectively suppresses noise and scanning artifacts in thermographic images.
    • It preserves image shapes similar to the structuring element without introducing bias.
    • Demonstrated the influence of different structuring element shapes on image analysis.

    Conclusions:

    • The LOCO filter is a valuable tool for bias-free noise reduction in thermographic imaging.
    • It maintains the shape-preserving advantages of morphological techniques.
    • The choice of structuring element significantly impacts the analysis of thermographic data.