Modules:MedianFilter-Documentation-3.6

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Gallery of New Features

Module Name

Median Image Filter

Input Image
Median Filtered Image

General Information

Module Type & Category

Type: CLI

Category: Filtering.Denoising

Authors, Collaborators & Contact

  • Author: Bill Lorensen
  • Contact: bill.lorensen at gmail.com

Module Description

The MedianImageFilter is commonly used as a robust approach for noise reduction. This filter is particularly efficient against 'salt-and-pepper' noise. In other words, it is robust to the presence of gray-level outliers. MedianImageFilter computes the value of each output pixel as the statistical median of the neighborhood of values around the corresponding input pixel.

Usage

Examples, Use Cases & Tutorials

  • This module is used to reduce noise in an image. It is most effective in reducing additive salt-and-pepper noise without grossly shift the edge structures. It may, however, remove thin structures such as thin vessels when the "Neighborhood Size" is too big.
  • A command line example of running this module is
MedianImageFilter 
 --neighborhood 1,1,1 
 CTHeadAxial.nhdr MedianImageFilterTest.nhdr

Quick Tour of Features and Use

  • Input/output panel:
Input/Output panels

User selects an image as input upon which the medial filter will apply. User creates an output image to store the result. Upon completion, the output image will be displayed in the viewing panel.

  • Parameters panel:
Input/Output panels

User specifies the neighborhood radius in three dimensions (comma separated without spaces). The bigger the size, the smoother the resulting image and the poorer the fine structures are preserved.

  • Viewing panel:
Input/Output panels

Upon completion, the median filter result is displayed in the viewing panel.

Development

Dependencies

None other than the core Slicer3 modules for image IO and display.

Known bugs

None.

Usability issues

None.

Source code & documentation

Source Code: MedianImageFilter.cxx

XML Description: MedianImageFilter.xml

Test: MedianImageFilterTest.cxx

Documentation:

USAGE: 
./MedianImageFilter --help

./MedianImageFilter  [--returnparameterfile <std::string>]
                       [--processinformationaddress <std::string>] [--xml]
                       [--echo] [--neighborhood <std::vector<int>>] [--]
                       [--version] [-h] <std::string> <std::string>
 
Where: 

  --returnparameterfile <std::string>
    Filename in which to write simple return parameters (int, float,
    int-vector, etc.) as opposed to bulk return parameters (image,
    geometry, transform, measurement, table).

  --processinformationaddress <std::string>
    Address of a structure to store process information (progress, abort,
    etc.). (default: 0)

  --xml
    Produce xml description of command line arguments (default: 0)

  --echo
    Echo the command line arguments (default: 0)

  --neighborhood <std::vector<int>>
    The size of the neighborhood in each dimension (default: 1,1,1)

  --,  --ignore_rest
    Ignores the rest of the labeled arguments following this flag.

  --version
    Displays version information and exits.

  -h,  --help
    Displays usage information and exits.

  <std::string>
    (required)  Input volume to be filtered

  <std::string>
    (required)  Output filtered

  Description: The MedianImageFilter is commonly used as a robust approach
  for noise reduction. This filter is particularly efficient against
  'salt-and-pepper' noise. In other words, it is robust to the presence of
  gray-level outliers. MedianImageFilter computes the value of each output
  pixel as the statistical median of the neighborhood of values around the
  corresponding input pixel.

  Author(s): Bill Lorensen

  Acknowledgements: This command module was derived from
  Insight/Examples/Filtering/MedianImageFilter (copyright) Insight
  Software Consortium

More Information

Acknowledgment

This work is part of the National Alliance for Medical Image Computing (NAMIC), funded by the National Institutes of Health through the NIH Roadmap for Medical Research, Grant U54 EB005149. Information on the National Centers for Biomedical Computing can be obtained from National Centers for Biomedical Computing.

References