J 2021

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

ČAPEK, Martin, Michaela BLAŽÍKOVÁ, Ivan NOVOTNÝ, Helena CHMELOVÁ, David SVOBODA et. al.

Basic information

Original name

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

Authors

ČAPEK, Martin (203 Czech Republic), Michaela BLAŽÍKOVÁ (203 Czech Republic), Ivan NOVOTNÝ (203 Czech Republic), Helena CHMELOVÁ (203 Czech Republic), David SVOBODA (203 Czech Republic, guarantor, belonging to the institution), Barbora RADOCHOVÁ (203 Czech Republic), Jiří JANÁČEK (203 Czech Republic) and Ondrej HORVÁTH

Edition

Image Analysis & Stereology, International Society for Stereology & Image Analysis, 2021, 1580-3139

Other information

Language

English

Type of outcome

Článek v odborném periodiku

Field of Study

10201 Computer sciences, information science, bioinformatics

Country of publisher

Slovenia

Confidentiality degree

není předmětem státního či obchodního tajemství

References:

Impact factor

Impact factor: 0.683

RIV identification code

RIV/00216224:14330/21:00121362

Organization unit

Faculty of Informatics

UT WoS

000639563600002

Keywords in English

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

Tags

International impact, Reviewed
Změněno: 10/6/2021 22:19, doc. RNDr. David Svoboda, Ph.D.

Abstract

V originále

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.

Links

EF16_013/0001775, research and development project
Name: Modernizace a podpora výzkumných aktivit národní infrastruktury pro biologické a medicínské zobrazování Czech-BioImaging