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Alpha root filtering: new feature suggestion. #3982

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@iliailmer iliailmer commented Jun 28, 2019

Description

I would like to add a new feature: root filtering. The basic idea is to use the fast Fourier transform on the input image and then raise the magnitude of the result to the power of $alpha$ ($alpha$-root) which is a user-specified parameter. Then, the magnitude of the inverse transform is returned by the function.

The papers utilizing the feature are here, here, and here.

I listed the main reference in the description of the function:
A. K. Jain, Fundamentals of Digital Image Processing. Upper SaddleRiver, NJ: Prentice-Hall, 1989.

Checklist

For reviewers

  • Check that the PR title is short, concise, and will make sense 1 year
    later.
  • Check that new functions are imported in corresponding __init__.py.
  • Check that new features, API changes, and deprecations are mentioned in
    doc/release/release_dev.rst.
  • Consider backporting the PR with @meeseeksdev backport to v0.14.x

@pep8speaks
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pep8speaks commented Jun 28, 2019

Hello @iliailmer! Thanks for updating this PR. We checked the lines you've touched for PEP 8 issues, and found:

There are currently no PEP 8 issues detected in this Pull Request. Cheers! 🍻

Comment last updated at 2022-03-22 14:44:45 UTC

@emmanuelle
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Hi @iliailmer thank you for contributing high-quality code, and sorry for the time it took to start reviewing (don't hesitate to ping devs another time :-)). I'm a bit hesitant here because the alpha-root filtering papers do not have a lot of citations. Could you please explain the advantage of the method compared to existing skimage filters (gaussian blurring, unsharp_mask function for sharpening)?

@iliailmer
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Hi @emmanuelle , thank you for the response. I think the algorithm has additional benefits: it can bring out details in greyscale images, for instance when I run it on cameraman from skimage.data.camera image it brightens the image and brings out coat buttons, etc. it's also pretty fast.

Base automatically changed from master to main February 18, 2021 18:23
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5 participants