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Error Resilience Analysis for JPEG 2000
Kovalčík, Marek ; Klíma, Ondřej (referee) ; Bařina, David (advisor)
The aim of this thesis is to analyze modern image compression format of JPEG 2000. It analyzes the effect of error resilience mechanisms on image compression with different settings. The impact of using tag embedding to help repair damaged images or using compression modes to improve error resilience is examined here. Quality is evaluated by the PSNR metric that detects the similarity of compressed and reference file. Adding certain tags to the data stream or using certain compression modes should help secure the JPEG 2000 file against image reconstruction damage. To test this hipothesis, there was created a model that acidentally damage the compressed file and evaluate decompressed images. The Kakadu library, which provides efficient work with the JPEG 2000 format, is used for the work. The experimental data set consists of various photographs in uncompressed PPM format in smaller but also in higher resolutions. The result of this work is to find out which compression settings to use for which group of images to make the compression efficient and secure the best. The end of this thesis is devoted to comparison of error resilience of JPEG 2000 and CCSDS 122.0.
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Optimization Risk Modelling in Strategic Applications
Kovalčík, Marek ; Štětina, Josef (referee) ; Popela, Pavel (advisor)
The aim of this diploma thesis is to design and efficiently implement a framework to support optimization modelling. The emphasis is placed on two-stage stochastic optimization problems and performing calculations on large data. The computing core uses the GAMS system and with using its application interface and Python programming language, the user will be able to efficiently acquire and process input and output data. The separation of the data logic and the application logic then offers a wide range of options for testing and experimenting with a general model on dynamically changing input data. The thesis is also focused on an evaluation of the framework complexity. The framework performance was evaluated by measuring the time required to complete the required task for various use cases, on the increasing sample size of input data.
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Optimization Risk Modelling in Strategic Applications
Kovalčík, Marek ; Štětina, Josef (referee) ; Popela, Pavel (advisor)
The aim of this diploma thesis is to design and efficiently implement a framework to support optimization modelling. The emphasis is placed on two-stage stochastic optimization problems and performing calculations on large data. The computing core uses the GAMS system and with using its application interface and Python programming language, the user will be able to efficiently acquire and process input and output data. The separation of the data logic and the application logic then offers a wide range of options for testing and experimenting with a general model on dynamically changing input data. The thesis is also focused on an evaluation of the framework complexity. The framework performance was evaluated by measuring the time required to complete the required task for various use cases, on the increasing sample size of input data.
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Error Resilience Analysis for JPEG 2000
Kovalčík, Marek ; Klíma, Ondřej (referee) ; Bařina, David (advisor)
The aim of this thesis is to analyze modern image compression format of JPEG 2000. It analyzes the effect of error resilience mechanisms on image compression with different settings. The impact of using tag embedding to help repair damaged images or using compression modes to improve error resilience is examined here. Quality is evaluated by the PSNR metric that detects the similarity of compressed and reference file. Adding certain tags to the data stream or using certain compression modes should help secure the JPEG 2000 file against image reconstruction damage. To test this hipothesis, there was created a model that acidentally damage the compressed file and evaluate decompressed images. The Kakadu library, which provides efficient work with the JPEG 2000 format, is used for the work. The experimental data set consists of various photographs in uncompressed PPM format in smaller but also in higher resolutions. The result of this work is to find out which compression settings to use for which group of images to make the compression efficient and secure the best. The end of this thesis is devoted to comparison of error resilience of JPEG 2000 and CCSDS 122.0.
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