Abstract
This paper models a texture as a 2D map** onto a nonlinear manifold representing the local structures of the image. This manifold is learned from the set of local patches from an exemplar texture. A multiscale decomposition of this manifold valued representation is computed that mimics the orthogonal wavelet transform. The key ingredient of this decomposition is a geometric association field that drives the computations along the manifold. Iterated predictions leads to the computation of details coefficients over the features manifold. The resulting transform is invertible, non-linear and represents efficiently the local geometric structures of the exemplar. The multiscale coefficients of this transform are used to perform analysis and synthesis of textures.
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Peyré, G. (2007). Texture Synthesis and Modification with a Patch-Valued Wavelet Transform. In: Sgallari, F., Murli, A., Paragios, N. (eds) Scale Space and Variational Methods in Computer Vision. SSVM 2007. Lecture Notes in Computer Science, vol 4485. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72823-8_55
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DOI: https://doi.org/10.1007/978-3-540-72823-8_55
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