Parallel implementation of an integrated edge-preserving smoothing algorithm in clusters of workstations

Chih Cheng Hung; Asim YarKhan; Kwai Wong; S. A. von Laven; Tommy Coleman

doi:10.1145/275295.283931

Parallel implementation of an integrated edge-preserving smoothing algorithm in clusters of workstations

Chih Cheng Hung, Asim YarKhan, Kwai Wong, S. A. von Laven, Tommy Coleman

Research output: Contribution to conference › Paper › peer-review

Abstract

An iterative, adaptive image smoothing algorithm may be time-consuming for a large amount of remotely sensed images. Because of the high computational cost of this type of algorithm it is essential for the algorithm to be implemented and evaluated in a parallel processing framework. The Message Passing Interface (MPI) running on an Ethernet connected network of workstations was tested on the image smoothing filter. Depending on the size of the image, MPI can reduce the computation-oriented algorithm significantly by properly selecting a number of processors. Testing results on different numbers of processors for the image smoothing filter were shown in this study.

Original language	English
Pages	20-22
Number of pages	3
DOIs	https://doi.org/10.1145/275295.283931
State	Published - 1998
Externally published	Yes
Event	Proceedings of the 1998 36th Annual Southeast Conference - Marietta, GA, USA Duration: Apr 1 1998 → Apr 3 1998

Conference

Conference	Proceedings of the 1998 36th Annual Southeast Conference
City	Marietta, GA, USA
Period	04/1/98 → 04/3/98

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title = "Parallel implementation of an integrated edge-preserving smoothing algorithm in clusters of workstations",

abstract = "An iterative, adaptive image smoothing algorithm may be time-consuming for a large amount of remotely sensed images. Because of the high computational cost of this type of algorithm it is essential for the algorithm to be implemented and evaluated in a parallel processing framework. The Message Passing Interface (MPI) running on an Ethernet connected network of workstations was tested on the image smoothing filter. Depending on the size of the image, MPI can reduce the computation-oriented algorithm significantly by properly selecting a number of processors. Testing results on different numbers of processors for the image smoothing filter were shown in this study.",

author = "Hung, {Chih Cheng} and Asim YarKhan and Kwai Wong and {von Laven}, {S. A.} and Tommy Coleman",

year = "1998",

doi = "10.1145/275295.283931",

language = "English",

pages = "20--22",

note = "Proceedings of the 1998 36th Annual Southeast Conference ; Conference date: 01-04-1998 Through 03-04-1998",

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AU - Hung, Chih Cheng

AU - YarKhan, Asim

AU - Wong, Kwai

AU - von Laven, S. A.

AU - Coleman, Tommy

PY - 1998

Y1 - 1998

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AB - An iterative, adaptive image smoothing algorithm may be time-consuming for a large amount of remotely sensed images. Because of the high computational cost of this type of algorithm it is essential for the algorithm to be implemented and evaluated in a parallel processing framework. The Message Passing Interface (MPI) running on an Ethernet connected network of workstations was tested on the image smoothing filter. Depending on the size of the image, MPI can reduce the computation-oriented algorithm significantly by properly selecting a number of processors. Testing results on different numbers of processors for the image smoothing filter were shown in this study.

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T2 - Proceedings of the 1998 36th Annual Southeast Conference

Y2 - 1 April 1998 through 3 April 1998

ER -

Parallel implementation of an integrated edge-preserving smoothing algorithm in clusters of workstations

Abstract

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