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Sparsity Optimizati...
Sparsity Optimization in Design of Multidimensional Filter Networks
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- Andersson, Mats (författare)
- Linköpings universitet,Institutionen för medicinsk teknik,Tekniska högskolan,Medical Informatics
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- Burdakov, Oleg, 1953- (författare)
- Linköpings universitet,Optimeringslära,Tekniska högskolan
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- Knutsson, Hans (författare)
- Linköpings universitet,Medicinsk informatik,Tekniska högskolan
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- Zikrin, Spartak (författare)
- Linköpings universitet,Matematiska institutionen,Tekniska högskolan,Optimization
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(creator_code:org_t)
- Linköping : Linköping University Electronic Press, 2013
- Engelska 21 s.
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Serie: LiTH-MAT-R, 0348-2960 ; 2013:16
- Relaterad länk:
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https://liu.diva-por... (primary) (Raw object)
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https://urn.kb.se/re...
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Abstract
Ämnesord
Stäng
- Filter networks is a powerful tool used for reducing the image processing time, while maintaining its reasonably high quality.They are composed of sparse sub-filters whose low sparsity ensures fast image processing.The filter network design is related to solvinga sparse optimization problem where a cardinality constraint bounds above the sparsity level.In the case of sequentially connected sub-filters, which is the simplest network structure of those considered in this paper, a cardinality-constrained multilinear least-squares (MLLS) problem is to be solved. If to disregard the cardinality constraint, the MLLS is typically a large-scale problem characterized by a large number of local minimizers. Each of the local minimizers is singular and non-isolated.The cardinality constraint makes the problem even more difficult to solve.An approach for approximately solving the cardinality-constrained MLLS problem is presented.It is then applied to solving a bi-criteria optimization problem in which both thetime and quality of image processing are optimized. The developed approach is extended to designing filter networks of a more general structure. Its efficiency is demonstrated by designing certain 2D and 3D filter networks. It is also compared with the existing approaches.
Ämnesord
- NATURVETENSKAP -- Matematik -- Beräkningsmatematik (hsv//swe)
- NATURAL SCIENCES -- Mathematics -- Computational Mathematics (hsv//eng)
- TEKNIK OCH TEKNOLOGIER -- Medicinteknik -- Medicinsk bildbehandling (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Medical Engineering -- Medical Image Processing (hsv//eng)
- TEKNIK OCH TEKNOLOGIER -- Elektroteknik och elektronik -- Signalbehandling (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Electrical Engineering, Electronic Engineering, Information Engineering -- Signal Processing (hsv//eng)
Nyckelord
- Sparse optimization; Cardinality Constraint; Multicriteria Optimization; Multilinear Least-Squares Problem; Filter networks; Medical imaging
Publikations- och innehållstyp
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