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Deconvolution fluorescence microscopy of yeast cells
Štec, Tomáš ; Plášek, Jaromír (advisor) ; Heřman, Petr (referee)
Title: Deconvolution fluorescence microscopy of yeast cells Author: Tomáš Štec Department: Institute of Physics of Charles University Supervisor: prof. RNDr. Jarmoír Plášek, CSc., Institute of Physics of Charles Uni- versity Abstract: Fluorescence microscopy presents an fast and cheap alternative to more advanced imaging methods like confocal and electron microscopy, even though it is subject to heavy image distortion. It is possible to recover most of the original distortion-free image using deconvolution in computer image processing. This al- lows reconstruction of 3D structure of studied objects. Deconvolution procedure of NIS Elements AR program undergoes an thorough inspection in this diploma the- sis. It is then applied on restoration of 3D structure of calcofluor stained cell wall of budding yeast Saccharomyces cerevisiae. Changes of the structure of the cell wall during cell ageing are being examined. Cell wall of aged cells shows increased surface roughness and even ruptures at the end of cell life. Keywords: fluorescence, microscopy, deconvolution, NIS Elements AR, calcofluor, yeast, cell wall, ageing
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Image Deblurring in Demanding Conditions
Kotera, Jan ; Šroubek, Filip (advisor) ; Portilla, Javier (referee) ; Jiřík, Radovan (referee)
Title: Image Deblurring in Demanding Conditions Author: Jan Kotera Department: Institute of Information Theory and Automation, Czech Academy of Sciences Supervisor: Doc. Ing. Filip Šroubek, Ph.D., DSc., Institute of Information Theory and Automation, Czech Academy of Sciences Abstract: Image deblurring is a computer vision task consisting of removing blur from image, the objective is to recover the sharp image corresponding to the blurred input. If the nature and shape of the blur is unknown and must be estimated from the input image, image deblurring is called blind and naturally presents a more difficult problem. This thesis focuses on two primary topics related to blind image deblurring. In the first part we work with the standard image deblurring based on the common convolution blur model and present a method of increasing robustness of the deblur- ring to phenomena violating the linear acquisition model, such as for example inten- sity clipping caused by sensor saturation in overexposed pixels. If not properly taken care of, these effects significantly decrease accuracy of the blur estimation and visual quality of the restored image. Rather than tailoring the deblurring method explicitly for each particular type of acquisition model violation we present a general approach based on flexible automatic...
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Demosaicing as an ill-posed inverse problem
Mariničová, Veronika ; Šroubek, Filip (advisor) ; Hnětynková, Iveta (referee)
Color information of a scene is only recorded partially by a digital camera.Specifically, only one of the red, green, and blue color components is sampled at each pixel.The missing color values must be estimated － a process called demosaicing. Demosaicing can be solved as an individual step in the image processing pipeline. In this case, any errors and artefacts produced by this step are carried over into further steps in the image processing pipeline and are possibly magnified. Alternatively, we can try to resolve several degradations at once in a joint solution, which eliminates this effect. We present one such solution, that in addition to demosaicing, also jointly solves denoising, deconvolution, and super-resolution in the form of a convex optimization problem. We provide an overview of demosaicing methods and evaluate the results from our solution against selected existing methods.
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Bioinformatical analysis of the complex multidimensional microscopy datasets
Backová, Lenka ; Černý, Jan (advisor) ; Čapek, Martin (referee)
Microscopy is embedded in the history of life sciences and vice versa. Recent advances in the field present new challenges as new revolutionary technologies arise. Sample prepa- ration, microscope operation and data analysis have become particularly demanding re- quiring specific interdisciplinary expertise. Bioimaging data analysis is computationally demanding, as microscopy technologies can easily acquire data of exceptional size, often in terabytes. Correct analysis requires computer vision knowledge, as well as knowledge of studied biological systems and last, but not least deep understanding of microscopy technology. Tools available for the analysis of the imaging data vary from open-source customizable software with a coverage of multiple tasks to a task specific proprietary software. To choose the best tools for the analysis, analysts should know their options and tasks at hand. In bioimage analysis the tasks needed to be employed depend on the desired outcome and the acquisition technology. Amongst the possible tasks to con- sider belong deconvolution, segmentation and registration. Amount of approaches and algorithms available is progressively growing, resulting in a complex field, difficult to be easily familiar with. My thesis covers different microscopy technologies with emphasis on...
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Deconvolution fluorescence microscopy of yeast cells
Štec, Tomáš ; Plášek, Jaromír (advisor) ; Heřman, Petr (referee)
Title: Deconvolution fluorescence microscopy of yeast cells Author: Tomáš Štec Department: Institute of Physics of Charles University Supervisor: prof. RNDr. Jarmoír Plášek, CSc., Institute of Physics of Charles Uni- versity Abstract: Fluorescence microscopy presents an fast and cheap alternative to more advanced imaging methods like confocal and electron microscopy, even though it is subject to heavy image distortion. It is possible to recover most of the original distortion-free image using deconvolution in computer image processing. This al- lows reconstruction of 3D structure of studied objects. Deconvolution procedure of NIS Elements AR program undergoes an thorough inspection in this diploma the- sis. It is then applied on restoration of 3D structure of calcofluor stained cell wall of budding yeast Saccharomyces cerevisiae. Changes of the structure of the cell wall during cell ageing are being examined. Cell wall of aged cells shows increased surface roughness and even ruptures at the end of cell life. Keywords: fluorescence, microscopy, deconvolution, NIS Elements AR, calcofluor, yeast, cell wall, ageing
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Použití gyroskopů a akcelerometrů k doostření fotografií pořízených mobilním telefonem
Šindelář, Ondřej ; Šroubek, Filip (advisor) ; Wilkie, Alexander (referee)
Long exposure handheld photography is coupled with the problem of blurring, which is difficult to remove without additional information. The goal of this work was to utilize motion sensors contained in modern smartphones to detect exact motion track of the image sensor during the exposure and then to remove the blur from the resulting photograph according to this data. A system was proposed which performs deconvolution using a kernel from the recorded gyroscope data. An implementation on Android platform was proved on a test smartphone device.
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Odstranění rozmazání pomocí dvou snímků s různou délkou expozice
Sabo, Jozef ; Šroubek, Filip (advisor) ; Horáček, Jan (referee)
In the presented work we study methods of image deblurring using two images of the same scene with different exposure times, focusing on two main approach categories, the so called deconvolution and non-deconvolution methods. We present theoretical backgrounds on both categories and evaluate their limitations and advantages. We dedicate one section to a comparison of both method categories on test data (images) for which we use a MATLAB implementation of the methods. We also compare the effectiveness of said methods against the results of a selected single- image de-noising algorithm. We do not focus at computational efficiency of algorithms and work with grayscale images only.
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Odstranění rozmazání pomocí dvou snímků s různou délkou expozice
Sabo, Jozef ; Šroubek, Filip (advisor) ; Horáček, Jan (referee)
In the presented work we study the methods of image deblurring using two images of the same scene with different exposure times, focusing on two main approach categories, so called deconvolution and non-deconvolution methods. We present theoretical backgrounds on both categories and evaluate their limitations and advantages. We dedicate one section to compare both method categories on test data (images) for which we our MATLAB implementation of the methods. We also compare the effectiveness of said methods against the results of a selected single-image de-noising algorithm. We do not focus at computational efficiency of algorithms and work with single-channel images only.
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Design of magnetic bar-code read head
Kadlčík, Libor ; Drexler, Petr (referee) ; Mikulka, Jan (advisor)
Magnetic bar-code is composed from ferromagnetic bars printed on a substrate. The amount of ferromagnetic material is low, therefore reading magnetic barcode requires sensitive methods. Principle of methods of sensing both low-intensity magnetic field (fluxgates) and detecting low concentration of ferromagnetic material (resonant circuit, differential sensor) will be described. There are sensors producing frequency-modulated signal, therefore we focus on frequency demodulators as well. Signal acquired by sensor suffers from convolution distortion, reconstruction methods will be introduced. The assembled device consists of sensing oscillator, frequency demodulator, amplifier and reconstructing circuit. Frequency demodulation is done by phase-locked loop or differential demodulator. Reconstruction is based on detection of inflection points, producing square signal (representing bars of barcode). Design of these blocks is described. The device is able to read magnetic barcodes and reconstruct convolutionary distorted acquired signal. The differential demodulator exhibits low noise and low temperature drift (contrary to phase-locked loop). Signal produced by reading 2 mm wide bars is reconstructed without any problems, bars of width less than 1 mm cause troubles in certain cases (due to high degree of convolution distortion).
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Three-Dimensional Reconstruction of Image in Digital Holographic Microscopy
Týč, Matěj ; Karásek,, Vítězslav (referee) ; Martišek, Dalibor (referee) ; Chmelík, Radim (advisor)
This thesis deals with the topic of 3D image processing for digital holographic microscopy - numerical refocusing. This method allows to perform mathematically accurate defocus correction on image of a sample captured away from the sample plane and it was applicable only for images that were made made using coherent illumination source. It has been generalized to a form in which it is also applicable to devices that use incoherent (non-monochromatic or extended) illumination sources. Another presented achievement concerns hologram processing. The advanced hologram processing method enables obtaining more data mainly concerning precision of quantities from one hologram — normally, one would have to capture multiple holograms to get those. Both methods have been verified experimentally.
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