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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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Audio restoration based on sparse signal representations
Záviška, Pavel ; Průša, Zdeněk (referee) ; Rajmic, Pavel (advisor)
This Master's Thesis deals with the issue of audio clipping and the application of sparse represenations model for the task of declipping. First, a general theory of clipping is described, followed by a brief overview of existing methods and a description of the general theory concerning sparse representations of signals and bases, respectively frames. Subsequently, two methods solving declipping problem based on sparse representations are intruduced. The first method uses the Generic proximal algorithm for convex optimization, the second one uses the Douglas-Rachford algorithm. The above mentioned methods have been programmed in the Matlab environment. The results of the declipping methods are evaluated according to SNR, PEMO-Q and also by subjective listening tests.
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Audio restoration based on sparse signal representations
Záviška, Pavel ; Průša, Zdeněk (referee) ; Rajmic, Pavel (advisor)
This Master's Thesis deals with the issue of audio clipping and the application of sparse represenations model for the task of declipping. First, a general theory of clipping is described, followed by a brief overview of existing methods and a description of the general theory concerning sparse representations of signals and bases, respectively frames. Subsequently, two methods solving declipping problem based on sparse representations are intruduced. The first method uses the Generic proximal algorithm for convex optimization, the second one uses the Douglas-Rachford algorithm. The above mentioned methods have been programmed in the Matlab environment. The results of the declipping methods are evaluated according to SNR, PEMO-Q and also by subjective listening tests.
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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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