19 April 2000 Multiscale scheme for image magnification
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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.
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Frederic Nicolier, Frederic Nicolier, Olivier Laligant, Olivier Laligant, Frederic Truchetet, Frederic Truchetet, } "Multiscale scheme for image magnification", Proc. SPIE 3974, Image and Video Communications and Processing 2000, (19 April 2000); doi: 10.1117/12.382986; https://doi.org/10.1117/12.382986

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