The walevet-based denoising of images in fiji, with exampleapplications in structured illumination microscopy

0542949 - ÚMG 2022 RIV SK eng J - Článek v odborném periodiku
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
Grant CEP: GA MŠk(CZ) LM2018129; GA MŠk(CZ) EF16_013/0001775; GA MŠk LO1419
Institucionální podpora: RVO:68378050
Klíčová slova: discrete wavelet transform * Fiji plugin * image filtration * structured illumination microscopy
Obor OECD: Computer hardware and architecture
Impakt faktor: 0.683, rok: 2021
Způsob publikování: Omezený přístup
https://www.ias-iss.org/ojs/IAS/article/view/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.
Trvalý link: http://hdl.handle.net/11104/0320272