Neural Networks versus Image Pyramids (bibtex)
by Horst Bischof, Walter G. Kropatsch
Abstract:
Neural networks and image pyramids are massively parallel processing structures. In this paper we exploit the similarities as well as the differences between these structures. The general goal is to exchange knowledge between these two fields. After introducing the basic concepts of neural networks and image pyramids we give a translation table of the vocabulary used in image pyramids and those used in neural networks. In the following sections we compare neural networks and image pyramids in detail. We show how a modified Hopfield network can be used for irregular decimation. We examine the type of knowledge stored and the processing performed by pyramids and neural networks. In the case of numerical information, so called 'numerical pyramids' are rather similar to neural networks. But also for 'symbolic pyramids' we show how to implement them by neural networks. In particular we present a neural implementation of the 2x2/2 curve pyramid. We derive some general rules for implementing symbolic pyramids by neural networks. Finally we briefly discuss the role of learning in image pyramids.
Reference:
Neural Networks versus Image Pyramids (Horst Bischof, Walter G. Kropatsch), Technical report, PRIP, TU Wien, 1993.
Bibtex Entry:
@TechReport{TR007,
  author =	 "Horst Bischof and Walter G. Kropatsch",
  institution =	 "PRIP, TU Wien",
  number =	 "PRIP-TR-007",
  title =	 "Neural {N}etworks versus {I}mage {P}yramids",
  year =	 "1993",
  url =		 "https://www.prip.tuwien.ac.at/pripfiles/trs/tr7.pdf",
  abstract =	 "Neural networks and image pyramids are massively
                  parallel processing structures. In this paper we
                  exploit the similarities as well as the differences
                  between these structures. The general goal is to
                  exchange knowledge between these two fields. After
                  introducing the basic concepts of neural networks
                  and image pyramids we give a translation table of
                  the vocabulary used in image pyramids and those used
                  in neural networks. In the following sections we
                  compare neural networks and image pyramids in
                  detail. We show how a modified Hopfield network can
                  be used for irregular decimation. We examine the
                  type of knowledge stored and the processing
                  performed by pyramids and neural networks. In the
                  case of numerical information, so called 'numerical
                  pyramids' are rather similar to neural networks. But
                  also for 'symbolic pyramids' we show how to
                  implement them by neural networks. In particular we
                  present a neural implementation of the 2x2/2 curve
                  pyramid. We derive some general rules for
                  implementing symbolic pyramids by neural
                  networks. Finally we briefly discuss the role of
                  learning in image pyramids.",
}
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