A Clustering Filter for Scale-Space Filtering and Image Restoration

Abstract

A nonlinear clustering filter is derived using the maximum entropy principle. This filter is governed by a single-scale parameter and uses local characteristics in the data to determine the scale parameter in the output space. It provides a mechanism for removing impulsive noise, preserving edges, and improving smoothing of nonimpulsive noise. It also presents a scheme for nonlinear scale-space filtering. Comparisons with Gaussian scale-space filtering are made using real images. It is demonstrated that the clustering filter gives much better results.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Cite

Text

Wong. "A Clustering Filter for Scale-Space Filtering and Image Restoration." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 1993. doi:10.1109/CVPR.1993.341036

Markdown

[Wong. "A Clustering Filter for Scale-Space Filtering and Image Restoration." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 1993.](https://mlanthology.org/cvpr/1993/wong1993cvpr-clustering/) doi:10.1109/CVPR.1993.341036

BibTeX

@inproceedings{wong1993cvpr-clustering,
  title     = {{A Clustering Filter for Scale-Space Filtering and Image Restoration}},
  author    = {Wong, Yiu-fai},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  year      = {1993},
  pages     = {668-669},
  doi       = {10.1109/CVPR.1993.341036},
  url       = {https://mlanthology.org/cvpr/1993/wong1993cvpr-clustering/}
}