0542949 - ÚMG 2022 RIV SK eng J - Journal Article
Čapek, Martin - Blažíková, Michaela - Novotný, Ivan - Chmelová, Helena - Svoboda, D. - Radochová, B. - Janáček, J. - Horváth, Ondřej
The walevet-based denoising of images in fiji, with exampleapplications in structured illumination microscopy.
Image Analysis and Stereology. Roč. 40, č. 1 (2021), s. 3-16. ISSN 1580-3139
R&D Projects: GA MŠMT(CZ) LM2018129; GA MŠMT(CZ) EF16_013/0001775; GA MŠMT LO1419
Institutional support: RVO:68378050
Keywords : discrete wavelet transform * Fiji plugin * image filtration * structured illumination microscopy
OECD category: Computer hardware and architecture
Impact factor: 0.683, year: 2021 ; AIS: 0.189, rok: 2021
Method of publishing: Limited access
Result website:
https://www.ias-iss.org/ojs/IAS/article/view/2432DOI: https://doi.org/10.5566/ias.2432

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.
Permanent Link: http://hdl.handle.net/11104/0320272