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Filtering methods for NMR measurements
Nezhyba, Jiří ; Mikulka, Jan (referee) ; Gescheidtová, Eva (advisor)
This master’s thesis deals with the wavelet transform and its use in processing and removing noise from images acquired by nuclear magnetic resonance. It defines fundamental terms for this work as mother wavelet or thresholding. Above all, it describes the principle of wavelet transform, thresholding techniques and criteria for evaluating the effectiveness of filtration. It describes the relation between wavelet transforms and digital filter banks. The experimental section describes the designed filtering method for removing noise from an image captured by the technique of nuclear magnetic resonance. We applied to different kinds of mother wavelets. Evaluation of the effectiveness of filtering was performed using the signal to noise ratio, relative contrast and the steepness of the intensity changes in signal intensity. It also discusses the comparison of properties of the image and selecting the mother wavelets based on image characteristics. Images were compared in terms of a histogram, cumulative histogram, k-space and the difference image.
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Retinal image processing using wavelet transform
Portyš, Jakub ; Kolář, Radim (referee) ; Taševský, Pavel (advisor)
Work is focused on usage wavelet transform in diagnostic of retinae illness. Wavelet transform enables decomposition of eye background pictures. With the following segmentation by force of thresholding it leads to lucidity of picture and simpler diagnostics of morphological and anatomical changes. Part of work is also familiarization with wavelet transform and mother's wavelet family. Marginally is in work analysed picture segmentation according to RGB coloured model, picture filtration and thresholding. In opening chapters are mentioned essential piece of knowledge from anatomy, physiology and pathology.
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Applications of wavelet transform in Mathematica and Sage
Novotný, Radek ; Trzos, Michal (referee) ; Rajmic, Pavel (advisor)
This thesis focuses on image processing using wavelet transform. The usage of wavelet transform is analysed especially for image compression and image noise reduction purposes. The analysis describes in detail aspects and application of the following wavelet transform methods: CWT, DWT, DTWT, 2D DWT. The thesis further explains the meaning of the mother wavelet and studies certain specific kinds of wavelets, kinds of thresholding and its purposes and also touches on the JPEG2000 standard. Mathematica and Sage software packages were used to design algorithms for image compression and image noise reduction, utilising relevant wavelet transform findings. The concluding part of the thesis compares the two software packages and results obtained using different algorithms.
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Retinal image processing using wavelet transform
Portyš, Jakub ; Kolář, Radim (referee) ; Taševský, Pavel (advisor)
Work is focused on usage wavelet transform in diagnostic of retinae illness. Wavelet transform enables decomposition of eye background pictures. With the following segmentation by force of thresholding it leads to lucidity of picture and simpler diagnostics of morphological and anatomical changes. Part of work is also familiarization with wavelet transform and mother's wavelet family. Marginally is in work analysed picture segmentation according to RGB coloured model, picture filtration and thresholding. In opening chapters are mentioned essential piece of knowledge from anatomy, physiology and pathology.
|
|
|
Applications of wavelet transform in Mathematica and Sage
Novotný, Radek ; Trzos, Michal (referee) ; Rajmic, Pavel (advisor)
This thesis focuses on image processing using wavelet transform. The usage of wavelet transform is analysed especially for image compression and image noise reduction purposes. The analysis describes in detail aspects and application of the following wavelet transform methods: CWT, DWT, DTWT, 2D DWT. The thesis further explains the meaning of the mother wavelet and studies certain specific kinds of wavelets, kinds of thresholding and its purposes and also touches on the JPEG2000 standard. Mathematica and Sage software packages were used to design algorithms for image compression and image noise reduction, utilising relevant wavelet transform findings. The concluding part of the thesis compares the two software packages and results obtained using different algorithms.
|
|
|
Applications of wavelet transform in Mathematica and Sage
Novotný, Radek ; Trzos, Michal (referee) ; Rajmic, Pavel (advisor)
This thesis focuses on image processing using wavelet transform. The usage of wavelet transform is analysed especially for image compression and image noise reduction purposes. The analysis describes in detail aspects and application of the following wavelet transform methods: CWT, DWT, DTWT, 2D DWT. The thesis further explains the meaning of the mother wavelet and studies certain specific kinds of wavelets, kinds of thresholding and its purposes and also touches on the JPEG2000 standard. Mathematica and Sage software packages were used to design algorithms for image compression and image noise reduction, utilising relevant wavelet transform findings. The concluding part of the thesis compares the two software packages and results obtained using different algorithms.
|
|
|
Filtering methods for NMR measurements
Nezhyba, Jiří ; Mikulka, Jan (referee) ; Gescheidtová, Eva (advisor)
This master’s thesis deals with the wavelet transform and its use in processing and removing noise from images acquired by nuclear magnetic resonance. It defines fundamental terms for this work as mother wavelet or thresholding. Above all, it describes the principle of wavelet transform, thresholding techniques and criteria for evaluating the effectiveness of filtration. It describes the relation between wavelet transforms and digital filter banks. The experimental section describes the designed filtering method for removing noise from an image captured by the technique of nuclear magnetic resonance. We applied to different kinds of mother wavelets. Evaluation of the effectiveness of filtering was performed using the signal to noise ratio, relative contrast and the steepness of the intensity changes in signal intensity. It also discusses the comparison of properties of the image and selecting the mother wavelets based on image characteristics. Images were compared in terms of a histogram, cumulative histogram, k-space and the difference image.
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