ML Anthology

Quadratic Filter and Feature Detection

Kae-Jy Chou, Brian G. Schunck
CVPR 1993 pp. 692-693
doi:10.1109/CVPR.1993.341024 /cvpr/1993/chou1993cvpr-quadratic/

Abstract

The quadratic filter for low-level vision applications is explored. The quadratic filter is the simplest nonlinear time-invariant filter and corresponds to the second term in the Volterra expansion. Concepts behind the quadratic filter are elaborated, and it is shown that it can be derived from fundamental properties of regions and the principle of model competition. Two properties of the filter are presented. It has better spatial localization than a linear filter, and it is insensitive to blurred boundaries.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

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Cite

Text

Chou and Schunck. "Quadratic Filter and Feature Detection." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 1993. doi:10.1109/CVPR.1993.341024

Markdown

[Chou and Schunck. "Quadratic Filter and Feature Detection." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 1993.](https://mlanthology.org/cvpr/1993/chou1993cvpr-quadratic/) doi:10.1109/CVPR.1993.341024

BibTeX

@inproceedings{chou1993cvpr-quadratic,
  title     = {{Quadratic Filter and Feature Detection}},
  author    = {Chou, Kae-Jy and Schunck, Brian G.},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  year      = {1993},
  pages     = {692-693},
  doi       = {10.1109/CVPR.1993.341024},
  url       = {https://mlanthology.org/cvpr/1993/chou1993cvpr-quadratic/}
}