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THE WAVELET-BASED DENOISING OF IMAGES IN FIJI, WITH EXAMPLE APPLICATIONS IN STRUCTURED ILLUMINATION MICROSCOPY
- 1.0542439 - FGÚ 2022 RIV SI eng J - Článek v odborném periodiku
Čapek, Martin - Blažíková, M. - Novotný, I. - Chmelová, H. - Svoboda, D. - Radochová, Barbora - Janáček, Jiří - Horváth, O.
THE WAVELET-BASED DENOISING OF IMAGES IN FIJI, WITH EXAMPLE APPLICATIONS IN STRUCTURED ILLUMINATION MICROSCOPY.
Image Analysis and Stereology. Roč. 40, č. 1 (2021), s. 3-16. ISSN 1580-3139
Grant CEP: GA MŠk(CZ) EF16_013/0001775; GA MŠk(CZ) LM2018129
Institucionální podpora: RVO:67985823
Klíčová slova: discrete wavelet transform * Fiji plugin * image filtration * structured illumination microscopy
Kód oboru RIV: BD - Teorie informace
Obor OECD: Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Impakt faktor: 0.682, rok: 2020
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/11104/0319850
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