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Products of "Edge-perts"
Images represent an important and abundant source of data. Understanding their statistical structure has important applications such as image compression and restoration. In this paper we propose a particular kind of probabilistic model, dubbed the “products of edge-perts model” to describe the structure of wavelet transformed images. We develop a practical denoising algorithm based on a single edge-pert and show state-ofthe-art denoising performance on benchmark images.
@inproceedings{5518, title = {Products of "Edge-perts"}, journal = {Advances in Neural Information Processing Systems 18: Proceedings of the 2005 Conference}, booktitle = {Advances in neural information processing systems 18}, abstract = {Images represent an important and abundant source of data. Understanding their statistical structure has important applications such as image compression and restoration. In this paper we propose a particular kind of probabilistic model, dubbed the “products of edge-perts model” to describe the structure of wavelet transformed images. We develop a practical denoising algorithm based on a single edge-pert and show state-ofthe-art denoising performance on benchmark images.}, pages = {419-426}, editors = {Weiss, Y. , B. Sch{\"o}lkopf, J. Platt}, publisher = {MIT Press}, organization = {Max-Planck-Gesellschaft}, school = {Biologische Kybernetik}, address = {Cambridge, MA, USA}, month = may, year = {2006}, slug = {5518}, author = {Gehler, PV. and Welling, M.}, month_numeric = {5} }