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Statistical based impulsive noise removal in digital radiography.

I Frosio1, N A Borghese

  • 1Computer Science Department, University of Milan, Via Comelico 39/41, 20135 Milan, Italy. frosio@dsi.unimi.it

IEEE Transactions on Medical Imaging
|January 1, 2009
PubMed
Summary

A novel filter effectively restores radiographic images degraded by impulsive noise. This method detects and corrects noise pulses, outperforming traditional techniques for clearer medical imaging.

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Area of Science:

  • Medical Imaging
  • Image Processing
  • Signal Processing

Background:

  • Radiographic images are often corrupted by impulsive noise, impacting diagnostic accuracy.
  • Impulsive noise, particularly from photon counting statistics, degrades image quality in digital radiography.
  • Existing noise reduction methods may not adequately address impulsive noise in radiographic images.

Purpose of the Study:

  • To introduce a new filter designed for restoring radiographic images affected by impulsive noise.
  • To develop a robust method for detecting and correcting impulsive noise in medical imaging.
  • To enable reliable estimation of sensor gain alongside noise reduction.

Main Methods:

  • A switching-based filter scheme is proposed, involving pulse detection and median filtering.

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  • A mixture model is utilized to describe the statistics of image noise, differentiating between photon counting and impulsive noise.
  • The filter's ability to estimate sensor gain is integrated into its operational framework.

    • Main Results:

    • The filter successfully restored both synthetic and real radiographic images corrupted by impulsive noise.
    • Experimental results confirmed the proposed filter's superior performance compared to traditional noise reduction methods.
    • The method demonstrated effective handling of noise statistics described by a mixture model.

    Conclusions:

    • The proposed filter offers a significant advancement in restoring noisy radiographic images.
    • This approach provides a more effective solution for impulsive noise removal in medical imaging applications.
    • The filter's ability to estimate sensor gain adds to its utility in radiographic image processing.