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231223s2001 xx |||||o 00| ||eng c |
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|a 10.1109/83.941860
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|a eng
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|a Muñoz, A
|e verfasserin
|4 aut
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|a Least-squares image resizing using finite differences
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|c 2001
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|a Text
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|a ƒaComputermedien
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|a ƒa Online-Ressource
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|a Date Completed 14.12.2009
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|a Date Revised 07.02.2008
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|a published: Print
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|a Citation Status PubMed-not-MEDLINE
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|a We present an optimal spline-based algorithm for the enlargement or reduction of digital images with arbitrary (noninteger) scaling factors. This projection-based approach can be realized thanks to a new finite difference method that allows the computation of inner products with analysis functions that are B-splines of any degree n. A noteworthy property of the algorithm is that the computational complexity per pixel does not depend on the scaling factor a. For a given choice of basis functions, the results of our method are consistently better than those of the standard interpolation procedure; the present scheme achieves a reduction of artifacts such as aliasing and blocking and a significant improvement of the signal-to-noise ratio. The method can be generalized to include other classes of piecewise polynomial functions, expressed as linear combinations of B-splines and their derivatives
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|a Journal Article
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|a Blu, T
|e verfasserin
|4 aut
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| 700 |
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|a Unser, M
|e verfasserin
|4 aut
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|i Enthalten in
|t IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
|d 1992
|g 10(2001), 9 vom: 15., Seite 1365-78
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|x 1941-0042
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|g volume:10
|g year:2001
|g number:9
|g day:15
|g pages:1365-78
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|u http://dx.doi.org/10.1109/83.941860
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