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Acceleration of Image Processing in GP-GPU Using OpenCl
Grim, Pavel ; Polok, Lukáš (referee) ; Zemčík, Pavel (advisor)
This work studies the possibility of obtaining the highest quality image from a video that contains a constant shot on one thing and proposes and creates a program that processes a video in this way. This work provides a description of several methods for improving the quality of images and algorithms on which some of these methods depend. The work also focuses on the usage of OpenCL standard. In this work there is a proposed and described program that processes the video and creates from it one better quality picture. At the end of this work there are outlined some possible continuations of this work.
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Automatic Selection of Representative Pictures
Bartoš, Peter ; Svoboda, Pavel (referee) ; Polok, Lukáš (advisor)
There are billions of photos on the internet and as the size of these digital repositories grows, finding target picture becomes more and more difficult. To increase the informational quality of photo albums we propose a new method that selects representative pictures from a group of photographs using computer vision algorithms. The aim of this study is to analyze the issues about image features, image similarity, object clustering and examine the specific characteristics of photographs. Tests show that there is no universal image descriptor that can easily simulate the process of clustering performed by human vision. The thesis proposes a hybrid algorithm that combines the advantages of selected features together using a specialized multiple-step clustering algorithm. The key idea of the process is that the frequently photographed objects are more likely to be representative. Thus, with a random selection from the largest photo clusters certain representative photos are obtained. This selection is further enhanced on the basis of optimization, where photos with better photographic properties are being preferred.
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Acceleration of Image Processing in GP-GPU Using OpenCl
Grim, Pavel ; Polok, Lukáš (referee) ; Zemčík, Pavel (advisor)
This work studies the possibility of obtaining the highest quality image from a video that contains a constant shot on one thing and proposes and creates a program that processes a video in this way. This work provides a description of several methods for improving the quality of images and algorithms on which some of these methods depend. The work also focuses on the usage of OpenCL standard. In this work there is a proposed and described program that processes the video and creates from it one better quality picture. At the end of this work there are outlined some possible continuations of this work.
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Automatic Selection of Representative Pictures
Bartoš, Peter ; Svoboda, Pavel (referee) ; Polok, Lukáš (advisor)
There are billions of photos on the internet and as the size of these digital repositories grows, finding target picture becomes more and more difficult. To increase the informational quality of photo albums we propose a new method that selects representative pictures from a group of photographs using computer vision algorithms. The aim of this study is to analyze the issues about image features, image similarity, object clustering and examine the specific characteristics of photographs. Tests show that there is no universal image descriptor that can easily simulate the process of clustering performed by human vision. The thesis proposes a hybrid algorithm that combines the advantages of selected features together using a specialized multiple-step clustering algorithm. The key idea of the process is that the frequently photographed objects are more likely to be representative. Thus, with a random selection from the largest photo clusters certain representative photos are obtained. This selection is further enhanced on the basis of optimization, where photos with better photographic properties are being preferred.
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