Stable Evaluation of Differential Operators and Linear and Nonlinear Multi-scale Filtering

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dc.contributor.authorScherzer, Otmar
dc.date.accessioned2018-11-04T22:10:35Z
dc.date.available2018-11-04T22:10:35Z
dc.date.issued1997-09-10
dc.description.abstractDiffusion processes create multi--scale analyses, which enable the generation of simplified pictures, where for increasing scale the image gets sketchier. In many practical applications the ``scaled image'' can be characterized via a variational formulation as the solution of a minimization problem involving unbounded operators. These unbounded operators can be evaluated by regularization techniques. We show that the theory of stable evaluation of unbounded operators can be applied to efficiently solve these minimization problems.
dc.description.departmentMathematics
dc.formatText
dc.format.extent12 pages
dc.format.medium1 file (.pdf)
dc.identifier.citationScherzer, O. (1997). Stable evaluation of differential operators and linear and nonlinear multi-scale filtering. <i>Electronic Journal of Differential Equations, 1997</i>(15), pp. 1-12.
dc.identifier.issn1072-6691
dc.identifier.urihttps://hdl.handle.net/10877/7772
dc.language.isoen
dc.publisherSouthwest Texas State University, Department of Mathematics
dc.rightsAttribution 4.0 International
dc.rights.holderThis work is licensed under a Creative Commons Attribution 4.0 International License.
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.sourceElectronic Journal of Differential Equations, 1997, San Marcos, Texas: Southwest Texas State University and University of North Texas.
dc.subjectNondifferntiable optimization problems
dc.subjectRegularization
dc.subjectInverse problems
dc.subjectImage reconstruction
dc.subjectBounded variation norm
dc.titleStable Evaluation of Differential Operators and Linear and Nonlinear Multi-scale Filtering
dc.typeArticle

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