A geometric framework for registration of sparse images

We examine the problem of image registration when images have a sparse representation in a dictionary of geometric features. We propose a novel algorithm for aligning images by pairing their sparse components. We show numerically that this algorithm works well in practice and analyze key properties on the dictionary that drive the registration performance. We compare these properties to existing characterizations of redundant dictionaries (i.e., coherence, restricted isometry property) and show that the newly introduced properties finely capture the behaviour of our registration algorithm.


Published in:
Proceedings of IEEE ICASSP, 1976-1980
Presented at:
International Conference in Speech, Acoustics and Signal Processing (ICASSP 2013), Vancouver, Canada, May 26-31, 2013
Year:
2013
Keywords:
Laboratories:




 Record created 2012-12-15, last modified 2018-09-13

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