Institute of Information Theory and Automation

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Department of Image Processing

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The Department is involved in basic research in image processing and pictorial pattern recognition. Major application areas are biomedicine, remote sensing, astronomy, and art conservation.

Main scientific areas
  • Recognition of distorted images and patterns by invariant descriptors regardless of their actual position in the scene
  • Registration and fusion of several images of the same scene taken at different times, by different sensors and/or from different viewpoints in order to obtain information of higher quality
  • Theory of moment invariants, namely of rotation invariants, affine invariants and invariants to convolution
  • Restoration of degraded images, namely multichannel blind deconvolution, edgepreserving denoising, local contrast enhancement, and color transformations
  • Image forensics - detection of image forgeries
  • Cultural heritage applications - cooperation with art conservators in order to facilitate the conservation and material analysis work
2017-02-08 12:55

Department detail

Ing. Michal Bartoš Ph.D.
RNDr. Zuzana Bílková
RNDr. Jan Blažek Ph.D.
Mgr. Jiří Boldyš Ph.D.
Mgr. Adam Dominec
Ing. Vít Hanousek
Dr. Barmak Honarvar Shakibaei Asli Ph.D.
RNDr. Cyril Höschl Ph.D.
Ing. Jan Kamenický Ph.D.
Ing. Tomáš Kerepecký
Ing. Jitka Kostková
RNDr. Jan Kotera
Mgr. Matěj Lébl
Ing. Babak Mahdian Ph.D.
Jiří Nábělek
Ing. Adam Novozámský Ph.D.
Mgr. Markéta Paroubková
Ing. Stanislav Saic CSc.
Dr. Ing. Jan Schier
RNDr. Michal Šorel Ph.D.
Ing. Lubomír Soukup Ph.D.
Doc. Ing. Filip Šroubek Ph.D. DSc.
Ing. Tomáš Suk Ph.D. DSc.
Jana Švarcová
Ing. Milan Talich Ph.D.
Bc. Oldřich Vlašic
Ing. Hynek Walner
RNDr. Aleš Zita
Doc. RNDr. Barbara Zitová Ph.D.
Duration: 2018 - 2020
The goal of the project is to develop new methods for colour image acquisition and processing and to apply the results of this research in selected practical applications. The project is aimed at colour image with high colour resolution, with up to several tens colour components.
Duration: 2018 - 2020
The topic of this project is to develop efficient algorithms for robust image description and for recovering a clear image from its degraded version.
Duration: 2017 - 2019
The basis of the project is the implementation of Industry 4.0 principles during production and repairs of constructional layers of surface transportation.The aim is the automation and optimization of the technological process of measuring and processing data about the surface of ground transportation by virtualization of all technological processes including the establishment of particular metho
Duration: 2017 - 2019
Digital image acquisition is often accompanied with its degradation by noise, blur (out-of-focus, motion etc.), compression, etc. In many cases, the degradation process can be modeled by a linear relation g=Hu+n where g denotes the acquired image, u the original image, H the degradation operator, and n random noise.
Duration: 2016 - 2018
Moment Invariants are one of the techniques of feature extraction frequently used for shape recognition algorithms. A moment is a projection of function into polynomial basis and Moment Invariant is a moment function retaining invariance to particular class of degradation (e.g. affine transformation, convolution with symmetric kernel, etc.).