Efficient Laplacian Feature Map Pyramids in a Hexagonal Framework

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Abstract

A systematic design procedure is used to develop Laplacian operators that facilitate the computation of hexagonal feature map pyramids. Our focus is the development of algorithms that can operate on hexagonal images over a range of scales. We show how scalable operators can be explicitly constructed using a Gaussian neighbourhood function. We extend this approach to achieve an efficient approximation via a feature map pyramid that implicitly embodies operator scaling. In both cases we provide performance evaluation with respect to edge localisation.
Original languageEnglish
Title of host publicationUnknown Host Publication
PublisherIEEE Signal Processing Society
Pages1466-1469
Number of pages4
ISBN (Print)978-1-4244-4296-6
Publication statusPublished (in print/issue) - 16 Mar 2010
EventIEEE International Conference on Acoustics, Speech and Signal Processing 2010 - Dallas, Texas
Duration: 16 Mar 2010 → …

Conference

ConferenceIEEE International Conference on Acoustics, Speech and Signal Processing 2010
Period16/03/10 → …

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