The Wavelet-Based Denoising Of Images in Fiji, With Example Applications in Structured Illumination Microscopy

Authors

  • Martin Čapek Institute of Molecular Genetics of the CAS Light Microscopy Core Facility https://orcid.org/0000-0002-5705-8196
  • Michaela Blažíková Institute of Molecular Genetics of the CAS Light Microscopy Core Facility
  • Ivan Novotný Institute of Molecular Genetics of the CAS Light Microscopy Core Facility
  • Helena Chmelová Institute of Molecular Genetics of the CAS Light Microscopy Core Facility
  • David Svoboda Masaryk University Faculty of Informatics Centre for Biomedical Image Analysis
  • Barbora Radochová Institute of Physiology of the CAS Laboratory of Biomathematics
  • Jiří Janáček Institute of Physiology of the CAS Laboratory of Biomathematics
  • Ondrej Horváth Institute of Molecular Genetics of the CAS Light Microscopy Core Facility

DOI:

https://doi.org/10.5566/ias.2432

Keywords:

discrete wavelet transform, Fiji plugin, image filtration, structured illumination microscopy

Abstract

Filtration of super-resolved microscopic images brings often troubles with removing undesired image parts like, e.g., noise, inhomogenous background and reconstruction artifacts. Standard filtration techniques, e.g., convolution- or Fourier transform-based methods are not always appropriate, since they may lower image resolution that was acquired by hi-tech and expensive microscopy systems. Thus, in this article it is proposed to filter such images using discrete wavelet transform (DWT). Newly developed Wavelet_Denoise plugin for free available Fiji software package demonstrates important possibilities of applying DWT to images: Decomposition of a filtered picture using various wavelet filters and levels of details with showing decomposed images and visualization of effects of back transformation of the picture with chosen level of suppression or denoising of wavelet coefficients. The Fiji framework allows, for example, using a plethora of various microscopic image formats for data opening, users can easily install the plugin through a menu command and the plugin supports processing 3D images in Z-stacks. The application of the plugin for removal of reconstruction artifacts and undesirable background in images acquired by super-resolved structured illumination microscopy is demonstrated as well.

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Published

2021-04-09

Issue

Vol. 40 No. 1 (2021)

Section

Original Research Paper

License

Copyright (c) 2021 Image Analysis & Stereology

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

How to Cite

Čapek, M., Blažíková, M., Novotný, I., Chmelová, H., Svoboda, D., Radochová, B., Janáček, J., & Horváth, O. (2021). The Wavelet-Based Denoising Of Images in Fiji, With Example Applications in Structured Illumination Microscopy. Image Analysis and Stereology, 40(1), 3-16. https://doi.org/10.5566/ias.2432

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