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dc.contributor.authorJOSHI, MVen_US
dc.contributor.authorCHAUDHURI, SUBHASISen_US
dc.date.accessioned2008-12-22T05:45:02Zen_US
dc.date.accessioned2011-11-28T02:47:47Zen_US
dc.date.accessioned2011-12-15T09:56:11Z
dc.date.available2008-12-22T05:45:02Zen_US
dc.date.available2011-11-28T02:47:47Zen_US
dc.date.available2011-12-15T09:56:11Z
dc.date.issued2004en_US
dc.identifier.citationProceedings of the International Conference on Image Processing (V 3), Singapore, 24-27 October 2004, 1775-1778en_US
dc.identifier.isbn0-7803-8554-3en_US
dc.identifier.uri10.1109/ICIP.2004.1421418en_US
dc.identifier.urihttp://hdl.handle.net/10054/445en_US
dc.identifier.urihttp://dspace.library.iitb.ac.in/xmlui/handle/10054/445en_US
dc.description.abstractWe propose a technique for super-resolution imaging of a scene from observations at different camera zooms. Given a sequence of images with different zoom factors of a static scene, we obtain a picture of the entire scene at a resolution corresponding to the most zoomed observation. We model the high resolution image as a simultaneous autoregressive (SAR) model, the parameters of which are learnt from the most zoomed observation. Assuming that the entire scene can be described by a homogeneous SAR model, the learnt parameters are then used in a suitable regularization technique to estimate the high resolution field.en_US
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.subjectImage Analysisen_US
dc.subjectImage Qualityen_US
dc.subjectRegression Analysisen_US
dc.subjectMathematical Modelsen_US
dc.titleZoom based super-resolution through SAR model fittingen_US
dc.typeArticleen_US
dc.description.copyright© IEEEen_US


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