Local Reproducible Smoothing Without Shrinkage

Oliensis, John

doi:10.1109/CVPR.1992.223263

Local Reproducible Smoothing Without Shrinkage

John Oliensis

CVPR 1992 pp. 277-282

doi:10.1109/CVPR.1992.223263 /cvpr/1992/oliensis1992cvpr-local/

Abstract

A simple local smoothing filter for curves or surfaces, combining the advantages of Gaussian smoothing and Fourier curve description, is defined. Unlike Gaussian filters, the filter described has no shrinkage problem. Repeated application of the filter does not yield a curve or surface smaller than the original, but simply reproduces the approximate result that would have been obtained by a single application at the largest scale. Unlike Fourier description, the filter is local in space. The wavelet transform of Y. Meyer (1989) is shown to have these properties.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>

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Cite

Text

Oliensis. "Local Reproducible Smoothing Without Shrinkage." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 1992. doi:10.1109/CVPR.1992.223263

Markdown

[Oliensis. "Local Reproducible Smoothing Without Shrinkage." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 1992.](https://mlanthology.org/cvpr/1992/oliensis1992cvpr-local/) doi:10.1109/CVPR.1992.223263

BibTeX

@inproceedings{oliensis1992cvpr-local,
  title     = {{Local Reproducible Smoothing Without Shrinkage}},
  author    = {Oliensis, John},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  year      = {1992},
  pages     = {277-282},
  doi       = {10.1109/CVPR.1992.223263},
  url       = {https://mlanthology.org/cvpr/1992/oliensis1992cvpr-local/}
}