Skip to content

Latest commit

 

History

History
40 lines (35 loc) · 2.03 KB

README.md

File metadata and controls

40 lines (35 loc) · 2.03 KB

Recursive bilateral filtering (developed by Qingxiong Yang) is pretty fast compared with most edge-preserving filtering methods

  • computational complexity is linear in both input size and dimensionality:
  • takes about 43 ms to process a one megapixel color image (i7 1.8GHz & 4GB mem)
  • about 18x faster than Fast high-dimensional filtering using the permutohedral lattice
  • about 86x faster than Gaussian kd-trees for fast high-dimensional filtering

Results


Original Image


OpenCV's BF (896ms)


RecursiveBF (18ms)


Gaussian Blur


Median Blur

For more details of the algorithm, please refer to the original paper

@inproceedings{yang2012recursive,
    title={Recursive bilateral filtering},
    author={Yang, Qingxiong},
    booktitle={European Conference on Computer Vision},
    pages={399--413},
    year={2012},
    organization={Springer}
}

Optionally, you can cite this repo

@misc{ming2017recursive,
    author = {Ming Yang},
    title = {A lightweight C++ library for recursive bilateral filtering},
    year = {2017},
    publisher = {GitHub},
    journal = {GitHub repository},
    howpublished = {\url{https://github.com/ufoym/RecursiveBF}}
}