Título:
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PSyCo: manifold span reduction for super resolution
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Autor/a:
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Pérez Pellitero, Eduardo; Salvador, Jordi; Ruiz Hidalgo, Javier; Rosenhahn, Bodo
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Otros autores:
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Universitat Politècnica de Catalunya. Departament de Teoria del Senyal i Comunicacions; Universitat Politècnica de Catalunya. GPI - Grup de Processament d'Imatge i Vídeo |
Abstract:
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The main challenge in Super Resolution (SR) is to discover the mapping between the low- and highresolution manifolds of image patches, a complex ill-posed problem which has recently been addressed through piecewise linear regression with promising results. In this paper we present a novel regression-based SR algorithm that benefits from an extended knowledge of the structure of both manifolds. We propose a transform that collapses the 16 variations induced from the dihedral group of transforms (i.e. rotations, vertical and horizontal reflections) and antipodality (i.e. diametrically opposed points in the unitary sphere) into a single primitive. The key idea of our transform is to study the different dihedral elements as a group of symmetries within the high-dimensional manifold. We obtain the respective set of mirror-symmetry axes by means of a frequency analysis of the dihedral elements, and we use them to collapse the redundant variability through a modified symmetry distance. |
Abstract:
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Peer Reviewed |
Materia(s):
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-Àrees temàtiques de la UPC::So, imatge i multimèdia::Creació multimèdia::Imatge digital -Computer vision -Experimental validations -Frequency Analysis -High resolution -High-dimensional -Ill posed problem -Piecewise linear regression -State of the art -Super resolution -Visió per ordinador |
Derechos:
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Tipo de documento:
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Artículo - Versión publicada Objeto de conferencia |
Editor:
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Institute of Electrical and Electronics Engineers (IEEE)
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