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Compressive Sensing With Prior Information Applied To Magnetic Resonance Imaging, Cristiano Jacques Miosso
Compressive Sensing With Prior Information Applied To Magnetic Resonance Imaging, Cristiano Jacques Miosso
Open Access Theses & Dissertations
This dissertation introduces the theory of compressive sensing with prior information about a signal's sparse representation. We show, mathematically and in numerical simulations, that prior information improves signal reconstruction, in terms of number of required measurements, computation time and signal-to-noise ratios. Following, we present a set of methods for enhanced magnetic resonance imaging and tomography that can be combined with prior information, for enhanced image quality.
In developing the theory of compressive sensing with prior information, we provide a mathematical proof of the required condition (in terms of number of linear measurements) for reconstruction using the ideal approach of l0-minimization, …
Evaluation Of An Image Processing Algorithm For Scene Change Detection, Daniel Flores
Evaluation Of An Image Processing Algorithm For Scene Change Detection, Daniel Flores
Open Access Theses & Dissertations
Despite the efforts to reduce traffic accidents by government entities and automobile manufactures, the numbers of accidents are not considerably reduced. An evaluation of an algorithm based on the fly's eye is done on this research applying its principles to detect scene change on images for printed circuit boards providing initial steps to implement this algorithm on vehicular traffic to keep track of objects moving on the field for collision avoidance purposes. The effectiveness of the algorithm is addressed through a comparison of its performance with that found in experimental data.