Subset average median estimator

Risto Suoranta; Kari-Pekka Estola

doi:10.1109/ISCAS.1993.393876

Subset average median estimator

Risto Suoranta, Kari-Pekka Estola

VTT Technical Research Centre of Finland

Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceedings › Scientific › peer-review

Abstract

Alternative interpretations and realizations for the subset averaged median estimators are discussed. Maximum noise suppression performance of the new filter class is achieved using the order statistic (OS)-filter realization. An alternative structure is obtained realizing the new filters directly in the sample domain. This leads to highly parallel realization of the new filters. The time domain interpretation of the subset averaging method allows adjustment of the time domain properties of the filters. The time domain weighting of the data within the window can be achieved using the samples to be weighted more often in the subsets than other samples. Midpoint weighting preserves the edges exactly, whereas uniform weighting results in gradual transition.

Original language	English
Title of host publication	1993 IEEE International Symposium on Circuits and Systems
Publisher	IEEE Institute of Electrical and Electronic Engineers
Number of pages	4
ISBN (Print)	0-7803-1281-3
DOIs	https://doi.org/10.1109/ISCAS.1993.393876
Publication status	Published - 1993
MoE publication type	A4 Article in a conference publication
Event	1993 IEEE International Symposium on Circuits and Systems (ICASSP '93) - Chicago, United States Duration: 25 Apr 1993 → 30 Apr 1993

Conference

Conference	1993 IEEE International Symposium on Circuits and Systems (ICASSP '93)
Country/Territory	United States
City	Chicago
Period	25/04/93 → 30/04/93

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10.1109/ISCAS.1993.393876

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title = "Subset average median estimator",

abstract = "Alternative interpretations and realizations for the subset averaged median estimators are discussed. Maximum noise suppression performance of the new filter class is achieved using the order statistic (OS)-filter realization. An alternative structure is obtained realizing the new filters directly in the sample domain. This leads to highly parallel realization of the new filters. The time domain interpretation of the subset averaging method allows adjustment of the time domain properties of the filters. The time domain weighting of the data within the window can be achieved using the samples to be weighted more often in the subsets than other samples. Midpoint weighting preserves the edges exactly, whereas uniform weighting results in gradual transition.",

author = "Risto Suoranta and Kari-Pekka Estola",

year = "1993",

doi = "10.1109/ISCAS.1993.393876",

language = "English",

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booktitle = "1993 IEEE International Symposium on Circuits and Systems",

publisher = "IEEE Institute of Electrical and Electronic Engineers",

address = "United States",

note = "1993 IEEE International Symposium on Circuits and Systems (ICASSP '93) ; Conference date: 25-04-1993 Through 30-04-1993",

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AU - Suoranta, Risto

AU - Estola, Kari-Pekka

PY - 1993

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N2 - Alternative interpretations and realizations for the subset averaged median estimators are discussed. Maximum noise suppression performance of the new filter class is achieved using the order statistic (OS)-filter realization. An alternative structure is obtained realizing the new filters directly in the sample domain. This leads to highly parallel realization of the new filters. The time domain interpretation of the subset averaging method allows adjustment of the time domain properties of the filters. The time domain weighting of the data within the window can be achieved using the samples to be weighted more often in the subsets than other samples. Midpoint weighting preserves the edges exactly, whereas uniform weighting results in gradual transition.

AB - Alternative interpretations and realizations for the subset averaged median estimators are discussed. Maximum noise suppression performance of the new filter class is achieved using the order statistic (OS)-filter realization. An alternative structure is obtained realizing the new filters directly in the sample domain. This leads to highly parallel realization of the new filters. The time domain interpretation of the subset averaging method allows adjustment of the time domain properties of the filters. The time domain weighting of the data within the window can be achieved using the samples to be weighted more often in the subsets than other samples. Midpoint weighting preserves the edges exactly, whereas uniform weighting results in gradual transition.

U2 - 10.1109/ISCAS.1993.393876

DO - 10.1109/ISCAS.1993.393876

M3 - Conference article in proceedings

SN - 0-7803-1281-3

BT - 1993 IEEE International Symposium on Circuits and Systems

PB - IEEE Institute of Electrical and Electronic Engineers

T2 - 1993 IEEE International Symposium on Circuits and Systems (ICASSP '93)

Y2 - 25 April 1993 through 30 April 1993

ER -

Subset average median estimator

Abstract

Conference

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