Image Deconvolution Using Multiple Sensors
dc.contributor.advisor | Baras, J.S. | en_US |
dc.contributor.author | Sidiropoulos, N.D. | en_US |
dc.contributor.department | ISR | en_US |
dc.date.accessioned | 2007-05-23T09:46:57Z | |
dc.date.available | 2007-05-23T09:46:57Z | |
dc.date.issued | 1990 | en_US |
dc.description.abstract | We consider the two dimensional Analytic Bezout Equation (ABE) and investigate the properties of a particular solution, based on certain conditions imposed on the convolution kernels. We use a family of suitably chosen sensors which besides being strongly coprime also satisfies additional technical conditions. The results permit the reconstruction of the original signal with arbitrarily good resolution, i.e. achieving arbitrarily large bandwidths, depending solely upon computational resources. The theoretical foundations of this technique provide a rigorous mathematical framework, and simulation results have been promising. The feasibility of construction reasonable good discrete-time, finite-bandwidth approximations has been established, and efficient Data Parallel Grid layouts that perform the required computation have been designed. A number of implementation problems arising out of the need to approximate a basically infinite computation have been addressed. | en_US |
dc.format.extent | 3041185 bytes | |
dc.format.mimetype | application/pdf | |
dc.identifier.uri | http://hdl.handle.net/1903/5040 | |
dc.language.iso | en_US | en_US |
dc.relation.ispartofseries | ISR; MS 1990-6 | en_US |
dc.subject | digital communications | en_US |
dc.subject | estimation | en_US |
dc.subject | filtering | en_US |
dc.subject | image processing | en_US |
dc.subject | signal processing | en_US |
dc.subject | parallel architectures | en_US |
dc.subject | Systems Integration | en_US |
dc.title | Image Deconvolution Using Multiple Sensors | en_US |
dc.type | Thesis | en_US |
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