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Proceedings Paper

Multiscale scheme for image magnification
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Paper Abstract

Using the wavelet transform (WT), a given signal is decomposed into a succession of embedded approximations and detail coefficients. The observation of the details shows that similarities can be noticed across scales, in particular for the transitions (edges in an image). A wavelet-based magnification that both increases the resolution of an image and adds high-frequency information is proposed in this paper. From a non-subsampled WT, the zero-crossings of the details coefficients provide a consistent representation. From these coefficients, a prediction of high-frequency coefficients is possible via the computation of local Liptschitz exponents but needs an interpolation due to the constancy of the number of details coefficients. The proposed magnification is based on the decimated Mallat's algorithm. As this transformation is not shift-invariant, the local laws cannot be computed. The prediction is realized via the learning of representative edge signatures. A multiscale database is therefore constructed from the edge's zero-crossings. The magnification quality is evaluated by application on synthetic and noisy images.

Paper Details

Date Published: 19 April 2000
PDF: 9 pages
Proc. SPIE 3974, Image and Video Communications and Processing 2000, (19 April 2000); doi: 10.1117/12.382986
Show Author Affiliations
Frederic Nicolier, IUT Le Creusot/Univ. de Bourgogne (France)
Olivier Laligant, IUT Le Cresuot/Univ. de Bourgogne (France)
Frederic Truchetet, IUT Le Creusot/Univ. de Bourgogne (France)


Published in SPIE Proceedings Vol. 3974:
Image and Video Communications and Processing 2000
Bhaskaran Vasudev; T. Russell Hsing; Andrew G. Tescher; Robert L. Stevenson, Editor(s)

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