Efficient Laplacian Feature Map Pyramids in a Hexagonal Framework

SA Coleman; BW Scotney; B Gardiner

Efficient Laplacian Feature Map Pyramids in a Hexagonal Framework

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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 language	English
Title of host publication	Unknown Host Publication
Publisher	IEEE Signal Processing Society
Pages	1466-1469
Number of pages	4
ISBN (Print)	978-1-4244-4296-6
Publication status	Published (in print/issue) - 16 Mar 2010
Event	IEEE International Conference on Acoustics, Speech and Signal Processing 2010 - Dallas, Texas Duration: 16 Mar 2010 → …

Conference

Conference	IEEE International Conference on Acoustics, Speech and Signal Processing 2010
Period	16/03/10 → …

Cite this

@inproceedings{11acbfcb54fc440299dc7cc2a3766a00,

title = "Efficient Laplacian Feature Map Pyramids in a Hexagonal Framework",

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.",

author = "SA Coleman and BW Scotney and B Gardiner",

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T1 - Efficient Laplacian Feature Map Pyramids in a Hexagonal Framework

AU - Coleman, SA

AU - Scotney, BW

AU - Gardiner, B

PY - 2010/3/16

Y1 - 2010/3/16

N2 - 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.

AB - 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.

M3 - Conference contribution

SN - 978-1-4244-4296-6

SP - 1466

EP - 1469

BT - Unknown Host Publication

PB - IEEE Signal Processing Society

T2 - IEEE International Conference on Acoustics, Speech and Signal Processing 2010

Y2 - 16 March 2010

ER -

Efficient Laplacian Feature Map Pyramids in a Hexagonal Framework

Abstract

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