Median Filtering in Constant Time
By Simon Perreault, Patrick Hébert. IEEE Transactions on Image Processing, 2007
344 citations recorded by the source corpus.
Subfields: Computer Vision and Pattern Recognition, Signal Processing
View Paper: https://www.semanticscholar.org/paper/a0a5a80e019c6eb501d32e4250b1be91dc27047e
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Computer Vision and Pattern Recognition
- Luc Van Gool
- Ming-Hsuan Yang
- Dacheng Tao
- Vladlen Koltun
- Xiaogang Wang
- Jitendra Malik
- Andrew Zisserman
- Chen Change Loy
In Signal Processing
- Yichen Wei
- Xiaoou Tang
- Vladlen Koltun
- Qifeng Chen
- Gerald Schaefer
- M. Emre Celebi
- Jean-Philippe Tarel
- William Van Stoecker
Citations in the corpus
- Fast visibility restoration from a single color or gray level image (2009, methodology): “In [9], a fast implementation of the median filter in O(sxsy) is proposed.”
- Constant Time Weighted Median Filtering for Stereo Matching and Beyond (2013, background): “The weighted median filter inherits some desired properties from both median filtering and edge-aware averaging filtering (the guided filter).”
- Guided Image Filtering (2010, methodology): “Because the moving histogram in [56] is proposed only for median filtering, the combination of [18]+[56], to the best of our knowledge, is an unpublished state-of-theart of bilateral filtering in the literature.”
- Lesion border detection in dermoscopy images (2009, methodology): “• Computational time: For the GF and MF, algorithms that perform in constant time independent of the mask size have been developed [13, 14].”
- Fast Image Processing with Fully-Convolutional Networks (2017, background): “Another family of dedicated acceleration schemes addresses the median filter and its variants [72, 61, 54, 80].”