Implementation and Performance Analysis of Filternets

Today Image acquisition equipment produces huge amounts of data that needs to be processed. Often the data describes signals with a dimensionality higher then 2, as with ordinary images. This introduce a problem when it comes to process this high dimensional data since ordinary signal processing too...

Full description

Bibliographic Details
Main Author: Einarsson, Henrik
Format: Others
Language:English
Published: Linköpings universitet, Medicinsk informatik 2006
Subjects:
Online Access:http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-5601
id ndltd-UPSALLA1-oai-DiVA.org-liu-5601
record_format oai_dc
spelling ndltd-UPSALLA1-oai-DiVA.org-liu-56012013-01-08T13:45:50ZImplementation and Performance Analysis of FilternetsengEinarsson, HenrikLinköpings universitet, Medicinsk informatikLinköpings universitet, Tekniska högskolanInstitutionen för medicinsk teknik2006Filter networksparse filtersefficient filteringorientation estimationMedical informaticsMedicinsk informatikToday Image acquisition equipment produces huge amounts of data that needs to be processed. Often the data describes signals with a dimensionality higher then 2, as with ordinary images. This introduce a problem when it comes to process this high dimensional data since ordinary signal processing tools are no longer suitable. New faster and more efficient tools need to be developed to fully exploit the advantages with e. g. a 3D CT-scan. One such tool is filternets, a layered networklike structure, which the signal propagates through. A filternet has three fundamental advantages which will decrease the filtering time. The network structure allows complex filter to be decomposed into simpler ones, intermediate result may be reused and filters may be implemented with very few nonzero coefficients (sparse filters). The aim of this study has been to create an implementation for filternets and optimize it with respect to execution time. Specially the possibility to use filternets that approximates a harmonic filterset for estimating orientation in 3D signals is investigated. Tests show that this method is up to about 30 times faster than a full filterset consisting of dense filters. They also show a slightly larger error in the estimated orientation compared with the dense filters, this error should however not limit the usability of the method. Student thesisinfo:eu-repo/semantics/bachelorThesistexthttp://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-5601application/pdfinfo:eu-repo/semantics/openAccess
collection NDLTD
language English
format Others
sources NDLTD
topic Filter network
sparse filters
efficient filtering
orientation estimation
Medical informatics
Medicinsk informatik
spellingShingle Filter network
sparse filters
efficient filtering
orientation estimation
Medical informatics
Medicinsk informatik
Einarsson, Henrik
Implementation and Performance Analysis of Filternets
description Today Image acquisition equipment produces huge amounts of data that needs to be processed. Often the data describes signals with a dimensionality higher then 2, as with ordinary images. This introduce a problem when it comes to process this high dimensional data since ordinary signal processing tools are no longer suitable. New faster and more efficient tools need to be developed to fully exploit the advantages with e. g. a 3D CT-scan. One such tool is filternets, a layered networklike structure, which the signal propagates through. A filternet has three fundamental advantages which will decrease the filtering time. The network structure allows complex filter to be decomposed into simpler ones, intermediate result may be reused and filters may be implemented with very few nonzero coefficients (sparse filters). The aim of this study has been to create an implementation for filternets and optimize it with respect to execution time. Specially the possibility to use filternets that approximates a harmonic filterset for estimating orientation in 3D signals is investigated. Tests show that this method is up to about 30 times faster than a full filterset consisting of dense filters. They also show a slightly larger error in the estimated orientation compared with the dense filters, this error should however not limit the usability of the method.
author Einarsson, Henrik
author_facet Einarsson, Henrik
author_sort Einarsson, Henrik
title Implementation and Performance Analysis of Filternets
title_short Implementation and Performance Analysis of Filternets
title_full Implementation and Performance Analysis of Filternets
title_fullStr Implementation and Performance Analysis of Filternets
title_full_unstemmed Implementation and Performance Analysis of Filternets
title_sort implementation and performance analysis of filternets
publisher Linköpings universitet, Medicinsk informatik
publishDate 2006
url http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-5601
work_keys_str_mv AT einarssonhenrik implementationandperformanceanalysisoffilternets
_version_ 1716528182122774528