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Modern restoration of audio containing missing portions
Skyva, Pavel ; Mangová, Marie (referee) ; Rajmic, Pavel (advisor)
This bachelor thesis deals with modern method of audio signal restoration. The reconstruction is primarily based on sparse signal representations. In thesis is described the way of searching sparse coefficients using proximal Douglas-Rachford algorithm and following computation of reconstructed signal using this coefficients. The algorithm of reconstruction is implemented in the MATLAB software with toolbox LTFAT included. Results of the reconstruction are compared using objective evaluation method Signal-to-Noise ratio (SNR).
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Methods for increasing bit-depth in images
Záviška, Pavel ; Koldovský, Zbyněk (referee) ; Rajmic, Pavel (advisor)
The goal of this bachelor thesis is the application of an issue of sparse representations on the task of increasing bit-depth in images. Standard methods for bit-depth expansion are described, subsequently a method using sparse representation of an image signal is introduced. Methods are programmed in the Matlab enviroment. The results of the methods implemented are compared by using PSNR, SSIM objective indexes and subjectively using an online questionnaire.
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Modern restoration of audio containing missing portions
Skyva, Pavel ; Mangová, Marie (referee) ; Rajmic, Pavel (advisor)
This bachelor thesis deals with modern method of audio signal restoration. The reconstruction is primarily based on sparse signal representations. In thesis is described the way of searching sparse coefficients using proximal Douglas-Rachford algorithm and following computation of reconstructed signal using this coefficients. The algorithm of reconstruction is implemented in the MATLAB software with toolbox LTFAT included. Results of the reconstruction are compared using objective evaluation method Signal-to-Noise ratio (SNR).
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Methods for increasing bit-depth in images
Záviška, Pavel ; Koldovský, Zbyněk (referee) ; Rajmic, Pavel (advisor)
The goal of this bachelor thesis is the application of an issue of sparse representations on the task of increasing bit-depth in images. Standard methods for bit-depth expansion are described, subsequently a method using sparse representation of an image signal is introduced. Methods are programmed in the Matlab enviroment. The results of the methods implemented are compared by using PSNR, SSIM objective indexes and subjectively using an online questionnaire.
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