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Title: | Compressive Sensing and Combinatorial algorithms for image compression |
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Author: | Arévalo López, Raúl |
Other authors: | Universitat Politècnica de Catalunya. Departament de Teoria del Senyal i Comunicacions; Boulgouris, Nikolaos |
Abstract: | Projecte final de carrera fet en col.laboració amb King's College London |
Abstract: | The initial motivation of this Masters Thesis is the design and analysis of an image compression method based on Compressive Sensing. Compressigve Sensing is a technique which allows coding sparse signals by projecting the signal onto random vectors. When signals are sparse, it is possible to encode the signal with a much smaller number of measurements than the length of the original signal. Two methods based on Compressive Sensing are proposed. Both of them initially apply a wavelet transform to obtain the signal in a convenient domain in which is supposed to be sparse. At the same time, in the wavelet transform domain some sub-blocks are generated, which are useful in order not to process the whole image, but sub-block per sub-block. The first method uses compressive sensing onto binary signals and the second one onto integers. By studying and testing the proposed methods, a new one not based on compressive sensing emerged which provided significant improvements. It is a combinatorial method which orders uniquely the possible combinations of a binary vector of length N with S nonzero coefficients. It is supported by a fast algorithm to cycle through the combinations. Results provided in this report allow having an idea of the efficiency and advantages and disadvantages of each one of the methods proposed. |
Subject(s): | -Àrees temàtiques de la UPC::So, imatge i multimèdia::Creació multimèdia::Imatge digital -Àrees temàtiques de la UPC::Enginyeria de la telecomunicació::Processament del senyal::Processament de la imatge i del senyal vídeo -Video -Imatges -- Compressió (Informàtica) -Vídeo |
Rights: | Attribution-NonCommercial-NoDerivs 3.0 Spain
http://creativecommons.org/licenses/by-nc-nd/3.0/es/ |
Document type: | Bachelor Thesis |
Published by: | Universitat Politècnica de Catalunya |
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