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Related Experiment Videos

Combination median filter.

A Kundu1, J Zhou

  • 1Dept. of Electr. Eng., State Univ. of New York at Buffalo, Amherst, NY.

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
|January 1, 1992
PubMed
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A new combination median filter preserves image details and structure. Using Dixon

Area of Science:

  • Image Processing
  • Computer Vision
  • Digital Signal Processing

Background:

  • Image smoothing is crucial for noise reduction.
  • Traditional filters often sacrifice image details.
  • Adaptive filters require complex local statistics computation.

Purpose of the Study:

  • Introduce a novel detail- and structure-preserving smoothing filter.
  • Develop a computationally efficient filtering algorithm.
  • Demonstrate superior performance compared to existing methods.

Main Methods:

  • The combination median filter integrates directional, multilevel, and standard median filters.
  • Dixon's r-test is employed for robust outlier detection to guide region selection.
  • A constant threshold for Dixon's test enables quasi-nonadaptive operation.

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Main Results:

  • The filter effectively smooths image regions while preserving fine details and structures.
  • Experimental results show superior performance over conventional smoothing filters.
  • The algorithm avoids the need for local statistics computation, enhancing efficiency.

Conclusions:

  • The combination median filter offers an effective and efficient solution for image smoothing.
  • Its detail- and structure-preserving capabilities make it suitable for various image processing applications.
  • The quasi-nonadaptive nature simplifies implementation and reduces computational load.