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Spiralet Sparse Representation

This is the first report on Working Paper WP-RFM-14-01. The potential and capability of sparse representations is well-known. However, their (multivariate variable) vectorial form, which is completely fine in many fields and disciplines, results in removal and filtering of important "spatial" relations that are implicitly carried by two-dimensional [or multi-dimensional] objects, such as images. In this paper, a new approach, called spiralet sparse representation, is proposed in order to develop an augmented representation and therefore a modified sparse representation and theory, which is capable to preserve the data associated to the spatial relations.

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Co-authorshipAuthorshipAuthorshipTopic signalWSpiralet Sparse Representationpreprint / 2014AReza Farrahi MoghaddamResearcherAMohamed CherietResearcherTComputer Vision30606 works
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Spiralet Sparse Representation

preprint / 2014

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