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Image, Information, Complexity. The study of visual information incorporating the function of information entropy with a focus on abstract art
Malečková, Dita ; Kera, Denisa (advisor) ; Marcelli, Miroslav (referee) ; Havel, Ivan M. (referee)
This text focuses on the relation of information and image, hence Information Theory and Image Analysis, as well as visualization of information and methods of visual analytics focusing on analysis of art works. It also concentrates on evolution of digital image and related new type of perception and artificial aesthetics. We narrow the broader topic of the image and image information to the abstract art, namely the work of Czech painter Frantisek Kupka, which is used as input in the experiment presenting original method of image analysis using the function of information entropy (Rényi entropy). This approach was used for the first time for analysis of art works with the aim to obtain the comparaison of natural and artificial classification of image information. We chose the work of abstract art not only with regard to given history of grammatics of abstract forms and its relation to the digital image, but also as an emblematic example of effective gaining of information from complex environment. Work thus summarizes historical context of evolution of digital image and theoretical reflection of contemporary image analytics and others techniques relevant to the image information and emphasizes relation of abstract art to the natural and simulated complexity.
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State trajectory approach to the interpretation of self-organization in the Belousov-Zhabotinsky reaction
ZHYROVA, Anna
The Belousov-Zhabotinsky reaction is a well-known model for investigating the self-organization manifestations in nature. The chemical reaction cascade is easy to control and measure in laboratory conditions, which makes the investigation of diverse scenarios of the system behavior possible. The aim of this thesis was to evaluate the course of the reaction under the assumption of multifractality of observed chemical patterns. The approach of the information entropy theory was applied to image analysis to assess the visible changes in the reaction oscillation. Furthermore, the new characteristics - point information gain entropy and point information gain entropy density - were also introduced. These values were used to construct the state trajectory of the complex system with unique oscillation states recognition by multivariate stochastic data analysis. The reliability of the developed approach was tested on numerous experiments, including the insufficiently-studied BZ reaction wave formation under the space constriction and distortion by re-shaking effect. It has been confirmed that each of the system states has its own characteristic spectrum of information entropy. The obtained state-trajectories for the BZ reaction allows researchers to study the changing system behavior in response to variation of the initial conditions and to make a prediction about state-trajectory evolution in the imminent future. It was showed that the information entropy calculation is an effective and cheap tool for non-invasive analysis of a wide range of self-organized systems. Finally, it may be implemented also to automate laborious tasks for different cell stage recognition in medicine and biology.
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Microscopy - Point Spread Function, Focus, Resolution
NÁHLÍK, Tomáš
The aim of this thesis was to design new algorithms for processing image data from microscopes and demonstration of the possibilities of their use on standard samples (latex particles of different diameter). Results were used for the analysis of real objects inside the living mammalian cell. For the design of these algorithms was necessary to first understand how the image in the microscope is build, including a variety of lens aberrations. It was necessary to start with simulations of ideal case displaying one point (simulation PSF). Images of Airy discs in the plane of focus, or simulations using the ENZ theory. Available ENZ simulations provide only a few sections of different focal planes. It was necessary to adjust them to a usable form for generating a full 3D view. Using these algorithms, it was examined the behavior of the basic lens aberrations, and the behavior of two particles (objects) at different distances from each other. At the conclusion of these observations, it was necessary to redefine the terms Focus and resolution. Furthermore, the definitions have been introduced for discriminability and distinguishability of objects in an image. Thanks to the new definitions and new viewing (information entropy) to challenge the discriminability/distinguishability problem of objects in the image was possible to design and develop algorithms for image processing that enable to detect objects below the Abbe resolution condition using standard optical bright field microscopy. It has been found experimentally that the limiting factor for resolution using this method is the size and resolution of the camera chip. When using a chip with a higher density of points, we can achieve better results (detection of smaller objects) using the same algorithms.
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