Multiscale decomposition using median and morphological filters

JA Bangham; RV Aldridge

doi:10.1109/NDSP.1993.767731

Multiscale decomposition using median and morphological filters

JA Bangham, RV Aldridge

School of Computing Sciences

Research output: Contribution to conference › Other

Abstract

The small differences between the output from cascades of multiscale median and morphological filters (datasieves) is explored. It is shown that the self dual nature median filters confers statistical verity and that open/close (close/open) filters have the advantage of yielding what appears to be a 1:1 transform pair. Overall, however, they distinguish ID patterns equally well from an uncorrelated noisy background.

Original language	English
Pages	6.1_1.1-6.1_1.4
Number of pages	4
DOIs	https://doi.org/10.1109/NDSP.1993.767731
Publication status	Published - Jan 1993
Event	IEEE Winter Workshop on Nonlinear Digital Signal Processing - Duration: 17 Jan 1993 → 20 Jan 1993

Conference

Conference	IEEE Winter Workshop on Nonlinear Digital Signal Processing
Period	17/01/93 → 20/01/93

Access to Document

10.1109/NDSP.1993.767731

Cite this

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title = "Multiscale decomposition using median and morphological filters",

abstract = "The small differences between the output from cascades of multiscale median and morphological filters (datasieves) is explored. It is shown that the self dual nature median filters confers statistical verity and that open/close (close/open) filters have the advantage of yielding what appears to be a 1:1 transform pair. Overall, however, they distinguish ID patterns equally well from an uncorrelated noisy background.",

author = "JA Bangham and RV Aldridge",

year = "1993",

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doi = "10.1109/NDSP.1993.767731",

language = "English",

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AU - Aldridge, RV

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AB - The small differences between the output from cascades of multiscale median and morphological filters (datasieves) is explored. It is shown that the self dual nature median filters confers statistical verity and that open/close (close/open) filters have the advantage of yielding what appears to be a 1:1 transform pair. Overall, however, they distinguish ID patterns equally well from an uncorrelated noisy background.

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DO - 10.1109/NDSP.1993.767731

M3 - Other

SP - 6.1_1.1-6.1_1.4

T2 - IEEE Winter Workshop on Nonlinear Digital Signal Processing

Y2 - 17 January 1993 through 20 January 1993

ER -