A Real-Time Edge-Preserving Denoising Filter

Simon Reich, Florentin Wörgötter, Babette Dellen

2018

Abstract

Even in todays world, where augmented reality glasses and 3d sensors become rapidly less expensive and widely more used, the most important sensor remains the 2d RGB camera. Every camera is an optical device and prone to sensor noise, especially in dark environments or environments with extreme high dynamic range. The here introduced filter removes a wide variation of noise, for example Gaussian noise and salt-and-pepper noise, but preserves edges. Due to the highly parallel structure of the method, the implementation on a GPU runs in real-time, allowing us to process standard images within tens of milliseconds. The filter is first tested on 2d image data and based on the Berkeley Image Dataset and Coco Dataset we outperform other standard methods. Afterwards, we show a generalization to arbitrary dimensions using noisy low level sensor data. As a result the filter can be used not only for image enhancement, but also for noise reduction on sensors like acceleremoters, gyroscopes, or GPS-trackers, which are widely used in robotic applications.

Paper Citation

in Harvard Style

Reich S., Wörgötter F. and Dellen B. (2018). A Real-Time Edge-Preserving Denoising Filter. In Proceedings of the 13th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2018) - Volume 4: VISAPP; ISBN 978-989-758-290-5, SciTePress, pages 85-94. DOI: 10.5220/0006509000850094

in Bibtex Style

@conference{visapp18,
author={Simon Reich and Florentin Wörgötter and Babette Dellen},
title={A Real-Time Edge-Preserving Denoising Filter},
booktitle={Proceedings of the 13th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2018) - Volume 4: VISAPP},
year={2018},
pages={85-94},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006509000850094},
isbn={978-989-758-290-5},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 13th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2018) - Volume 4: VISAPP
TI - A Real-Time Edge-Preserving Denoising Filter
SN - 978-989-758-290-5
AU - Reich S.
AU - Wörgötter F.
AU - Dellen B.
PY - 2018
SP - 85
EP - 94
DO - 10.5220/0006509000850094
PB - SciTePress