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Acceleration of Data Compression with Parallel Architectures
Juránek, Luboš ; Tříska, Vít (referee) ; Šimek, Václav (advisor)
This bachelor thesis deals with the use of parallel architectures, in particular the GPU, for acceleration of selected lossless compression algorithms, based on a statistical method, and transformations, which change the entropy of the input data to achieve better compression ratio. In this work there are in theory summarized general information about parallel architectures and programming options for them, mainly using NVIDIA CUDA and OpenCL.
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Lossless Image Compression
Komjáthy, Gergely ; Polok, Lukáš (referee) ; Bařina, David (advisor)
This thesis deals with lossless image compression. In this paper are shown some colour models, which can be used for lossless image compression and formulas how to convert them to RGB and vica versa. You can learn predictors, how they work and discription of some of them. There is described the function of arithmetic coder, PPM coder and a brief description of Huffman coding.
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Medical Image Data Compression
Šebek, Jiří ; Bařina, David (referee) ; Kršek, Přemysl (advisor)
This thesis deals with several lossless methods of image compression. The main goal is to achieve the best compression ratio for set of medical images. This paper provides brief introduction into the data compression theory. It also contains design of image compression and description of designed compression modules implementation. Also the verifi cation of suitability of designed method for medical images compression is involved.
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Compression Methods Based on Context Modelling
Gach, Tomáš ; Drábek, Vladimír (referee) ; Bařina, David (advisor)
The aim of this thesis is to describe basic properties of the context-based compression methods. Modelling procedure is presented together with the principle of an arithmetic coding. Gradually the PPM, CTW, and PAQ methods are introduced together with the possible implementation of the basic PPM probability model. The performance of context-based, dictionary and the most currently used methods of data compression is being compared. Based on obtained results, the possible usage of PPM methods is summarized.
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Lossless Video Compression
Němec, Jaroslav ; Polok, Lukáš (referee) ; Bařina, David (advisor)
This master's thesis deals with lossless video compression. This thesis includes basic concepts and techniques used in image representation. The reader can find an explanation of basic difference between lossless video compression and lossy video compression and lossless video compression limitations. There is also possible find a description of the basic blocks forming the video codec (every block is described in detail). In every block there are introduced its possible variants. Implemented lossless videocodec was compared with common lossless videocodecs.
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Lossless Light Field Compression
Navrátil, Robert ; Šolony, Marek (referee) ; Bařina, David (advisor)
This thesis is focused on lossless light-field images compression, where it could be viable to extend common predictors into more dimensions. First chapter is regarding to essential theory about light-field images and 4D light-field, which is followed by description of every predictor and coder. With this is connected description of used compression pipeline. Last chapters contains description of solution and differences between every predictor result and theirs dimensional variant. At the end the results are compared with PNG. The result is that some 4D variants of implemented predictors have better compression rate than PNG.
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Analysis of JPEG 2000 Settings
Mitaš, Matěj ; Klíma, Ondřej (referee) ; Bařina, David (advisor)
This thesis analyses settings of JPEG 2000 format. The aim is to find appropriate values for each setting. Main criteria are compression performance, elapsed time and used memory. There are two libraries used that are implementing JPEG 2000 format: Kakadu and OpenJPEG. Testing was secured by framework implemented in Python. Results of this thesis enable users to use JPEG 2000 more effectively and with deeper understanding of inner workings.
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Implementation of Statistical Compression Methods
Beněk, Tomáš ; Polok, Lukáš (referee) ; Bařina, David (advisor)
This thesis deals with the statistical compression methods. This work describes basic theoretical introduction to the data compression and the most important representatives of statistical methods. There is also described compression process based on the Burrows-Wheeler algorithm, which is implemented in the form of portable library in C++ programming language. This work compares effectiveness of each method on suitable data corpus, which contains various data types and according to achieved results discusses suitability of usage of methods and possible improvements.
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Lossless Video Compression
Kafka, Jan ; Polok, Lukáš (referee) ; Bařina, David (advisor)
This thesis is about the lossless video compression using 3D prediction. At first is introduced the necessary theory about image data modification. This part serves to define important terms, which are needed to start the creative work itself. Then several variants of codec's structure proposals follow, as well as the choice of methods and description of expected characteristics. Here we can get the first idea how the codec works. Then there is a description of some implementation's details, which could give a detailed insight into the codec's inner architecture. In the last part of the work, the implemented codec is tested and its characteristics are compared to another lossless codecs. The result is that the own codec, using the 3D prediction, can defeat all other tested codecs with its compression ratio.
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Lossless Light Field Compression
Navrátil, Robert ; Šolony, Marek (referee) ; Bařina, David (advisor)
This thesis is focused on lossless light-field images compression, where it could be viable to extend common predictors into more dimensions. First chapter is regarding to essential theory about light-field images and 4D light-field, which is followed by description of every predictor and coder. With this is connected description of used compression pipeline. Last chapters contains description of solution and differences between every predictor result and theirs dimensional variant. At the end the results are compared with PNG. The result is that some 4D variants of implemented predictors have better compression rate than PNG.
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