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Effect of Noise on Video Compression
Anton, Matyáš ; Drábek, Vladimír (referee) ; Bařina, David (advisor)
Videos are in fact image signals and as such, they are susceptible to distortions in the form of noise. This thesis' goal was to determine how the presence of noise can affect the results of image data compression as well as what impact might the lossy compression have on the noise present. Four contemporary compression formats were chosen, namely H.264, H.265, Motion JPEG 2000 and DIRAC, representing different approaches to the video compression, especially the contrast between a discrete cosine transform and a discrete wavelet transform.
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Image composition
Smital, Petr ; Petyovský, Petr (referee) ; Richter, Miloslav (advisor)
This thesis deals with methods of improving the quality of image output of an electron microscope by composing consecutive frames. The thesis contains a brief description of an electron microscope and the problems that deteriorate its image quality, and three basic mathematical algorithms that can be used to remove them. These are the simple averaging method, the method of least squares and the method of vector space. For all of the methods, the thesis describes ways of their implementation, the possibilities of their use and their mutual comparison. This thesis also deals with the problem of so-called superresolution, i.e. exceeding the physical resolution of a sensor using the methods mentioned above, and the problem of electron beam centring.
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Implementation of wavelet transform in C++
Valouch, Lukáš ; Hasmanda, Martin (referee) ; Beneš, Radek (advisor)
The aim of this thesis is implementation of wavelet transform algorithm for noise reduction. The noise reduction itself is focused on improving informative capabilities of sonographic (ultrasound) images in medicine. For this purpose, thresholding of detailed coefficients on individual levels of multiresolution analysis was used. Common procedures were not used for searching for the most suitable thresholds of those levels. The alternative concept's design is based on fundamental empirical approach, where the individual thresholds are optimised by evolution algorithms. However, with this algorithmic procedure, more problems manifest regarding the objective evaluation of the success of noise reduction. Because of this, the program uses commonly used parameters such as mean square error of the whole image, linear slope edge approximation, relative contrast of two differently bright and distinct points and the standard deviation of compact surface. Described theoretical knowledge is used in developed application DTWT. It executes multilevel decomposition and reversed reconstruction by discrete time wavelet transform, thresholding of detailed coefficients and final evaluation of performed noise reduction. The developed tool can be used separately to reduce noise. For our purposes, it has been modified in way, that it executed through the component for evolutionary optimization of parameters (Optimize Parameters) in created scenario in RapidMiner program. In the optimization process, this component used evaluation received from DTWT program as fitness function. Optimal thresholds were sought separately for three wavelet families - Daubeschies, Symmlets and Coiflets. The evolution algorithm chose soft threshold for all three wavelet families. In comparison to hard threshold, it is more suitable for noise reduction, but it has tendencies to blur the edges more. The devised method had in most cases greater evaluated success of noise reduction with wavelet transform with threshold search done by evolution algorithms, than commonly used filters. In visual comparison however the wavelet transform introduced some minor depreciating artefacts into the image. It is always about compromise between noise reduction and maximal preservation of image information. Objectively evaluating this dilemma is not easy and is always dependant on subjective viewpoint which in case of sonographic images is that of the attending physician.
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Text separation
Burlak, Vladimír ; Macho, Tomáš (referee) ; Richter, Miloslav (advisor)
This bachelor’s thesis describes basic methods of picture segmentation for the purpose of separation of text from a background. In first part are described general methods meant for picture processing. There is described verging, edge detection and interference reduction. In second part are defined categories of text in picture. Third part is focused on program which will help with picture segmentation.
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Optical Character Recognition
Bílek, Jan ; Žák, Pavel (referee) ; Zuzaňák, Jiří (advisor)
This work describes problems of optical character recognition and methods which are used to improve its results. It specializes in problems of image spam and its adjustment for its recognition. This work describes methods of processing an image which leads to better results of text recognition and also some methods used to the character recognition. There is also described a scheme and an implementation of a system which processes an image spam and detects a text within it.
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Image recognition for robotic hand
Labudová, Kristýna ; Jakubíček, Roman (referee) ; Harabiš, Vratislav (advisor)
This thesis concerns with processing of embedded terminals’ images and their classification. There is problematics of moire noise reduction thought filtration in frequency domain and the image normalization for further processing analyzed. Keypoints detectors and descriptors are used for image classification. Detectors FAST and Harris corner detector and descriptors SURF, BRIEF and BRISK are emphasized as well as their evaluation in terms of potential contribution to this work.
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Noise reduction in LASER source device for optical trap
Gajzler, Vojtěch ; Adámek, Roman (referee) ; Brablc, Martin (advisor)
This work focuses on the reduction of noise in a laser source to increase the efficiency of an optical trap. The first part describes the issue of noise, methods of noise suppression, and the Red Pitaya control board. The following section thoroughly describes the program development using Simulink and Xilinx Vivado. Furthermore, the method of noise reduction using a PI controller is described. The conclusion of the work is focused on evaluating the experiment to verify the effectiveness of noise reduction.
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Noise reduction in high resolution computed tomography data
Tkadlecová, Markéta ; Chmelík,, Jiří (referee) ; Zikmund, Tomáš (advisor)
Vzhledem ke komplexnosti procesu akvizice dat výpočetní tomografie (CT) je šum v rentgenových snímcích nevyhnutelný a může vést ke zkreslení získané informace. Proto by měl být co nejvíce potlačen. Dosud se výzkum zaměřoval především na redukci šumu v CT datech u lékařských CT s nízkými dávkami, zatímco o šumu a jeho potlačení v CT datech s vysokým rozlišením je známo jen málo. Tato redukce může probíhat v oblasti rentgenových snímků, v průběhu tomografické rekonstrukce nebo v oblasti tomografických řezů. Tato práce se zabývá především redukcí šumu v rentgenových snímcích a tomografických řezech. Prvním krokem k nalezení komplexní metodiky je určení rozdělení a matematického modelu šumu přítomného v rentgenových snímcích. Tento model byl určen pomocí snímků bez přítomného vzorku, které byly pořízeny s různými expozičními časy. Pomocí stanoveného modelu byl simulován šum ve fantomovém datasetu. Vybrané algoritmy byly testovány na projekčních snímcích a tomografických řezech fantomu a porovnávány jak subjektivně, tak objektivně pomocí metrik kvality obrazu. Strategie s nejlepšími výsledky byly dále testovány na naměřených CT datech z CT systému Rigaku nano3DX s vysokým rozlišením a byly popsány jejich výhody, omezení a možnosti využití.
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