Implicit Filtering for Image and Shape Processing
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2011Pay-Per-View via TIB Hannover:
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The main purpose of this paper consists of demonstrating advantages of using implicit filtering schemes (noncausal IIR filters, in the signal processing language) for some basic image processing and geometric modeling applications. In particular, applications of implicit filtering for curve subdivision, image filtering, estimating image derivatives, and deblurring Gaussian blur are considered.
BibTeX
@inproceedings {10.2312:PE:VMV:VMV11:277-283,
booktitle = {Vision, Modeling, and Visualization (2011)},
editor = {Peter Eisert and Joachim Hornegger and Konrad Polthier},
title = {{Implicit Filtering for Image and Shape Processing}},
author = {Belyaev, Alexander and Yamauchi, Hitoshi},
year = {2011},
publisher = {The Eurographics Association},
ISBN = {978-3-905673-85-2},
DOI = {10.2312/PE/VMV/VMV11/277-283}
}
booktitle = {Vision, Modeling, and Visualization (2011)},
editor = {Peter Eisert and Joachim Hornegger and Konrad Polthier},
title = {{Implicit Filtering for Image and Shape Processing}},
author = {Belyaev, Alexander and Yamauchi, Hitoshi},
year = {2011},
publisher = {The Eurographics Association},
ISBN = {978-3-905673-85-2},
DOI = {10.2312/PE/VMV/VMV11/277-283}
}