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Motion dependent spatiotemporal smoothing for noise reduction in very dim light image sequences

Malm, Henrik LU and Warrant, Eric LU (2006) 18th International Conference on Pattern Recognition, ICPR 2006 3. p.954-959
Abstract
A new method for noise reduction using spatiotemporal smoothing is presented in this paper. The method is developed especially for reducing the noise that arises when acquiring video sequences with a camera under very dim light conditions. The work is inspired by research on the vision of nocturnal animals and the adaptive spatial and temporal summation that is prevalent in the visual systems of these animals. From analysis using the so-called structure tensor in the three-dimensional spatiotemporal space, motion segmentation and global ego-motion estimation, Gaussian shaped smoothing kernels are oriented mainly in the direction of the motion and in spatially homogeneous directions. In static areas, smoothing along the temporal dimension... (More)
A new method for noise reduction using spatiotemporal smoothing is presented in this paper. The method is developed especially for reducing the noise that arises when acquiring video sequences with a camera under very dim light conditions. The work is inspired by research on the vision of nocturnal animals and the adaptive spatial and temporal summation that is prevalent in the visual systems of these animals. From analysis using the so-called structure tensor in the three-dimensional spatiotemporal space, motion segmentation and global ego-motion estimation, Gaussian shaped smoothing kernels are oriented mainly in the direction of the motion and in spatially homogeneous directions. In static areas, smoothing along the temporal dimension is favoured for maximum preservation of structure. The technique has been applied to various dim light image sequences and results of these experiments are presented here. (Less)
Please use this url to cite or link to this publication:
author
organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
keywords
Visual systems, Gaussian shaped smoothing kernels, Video sequences, Image sequences
host publication
Proceedings - International Conference on Pattern Recognition
volume
3
pages
954 - 959
publisher
IEEE--Institute of Electrical and Electronics Engineers Inc.
conference name
18th International Conference on Pattern Recognition, ICPR 2006
conference location
Hong Kong, China
conference dates
2006-08-20 - 2006-08-24
external identifiers
  • wos:000240705600230
  • scopus:34147142880
ISSN
1051-4651
DOI
10.1109/ICPR.2006.813
language
English
LU publication?
yes
id
8bf3b842-5c77-4005-b088-b4bb4ddd04f5 (old id 616788)
date added to LUP
2007-11-24 11:47:37
date last changed
2019-02-20 07:52:19
@inproceedings{8bf3b842-5c77-4005-b088-b4bb4ddd04f5,
  abstract     = {A new method for noise reduction using spatiotemporal smoothing is presented in this paper. The method is developed especially for reducing the noise that arises when acquiring video sequences with a camera under very dim light conditions. The work is inspired by research on the vision of nocturnal animals and the adaptive spatial and temporal summation that is prevalent in the visual systems of these animals. From analysis using the so-called structure tensor in the three-dimensional spatiotemporal space, motion segmentation and global ego-motion estimation, Gaussian shaped smoothing kernels are oriented mainly in the direction of the motion and in spatially homogeneous directions. In static areas, smoothing along the temporal dimension is favoured for maximum preservation of structure. The technique has been applied to various dim light image sequences and results of these experiments are presented here.},
  author       = {Malm, Henrik and Warrant, Eric},
  issn         = {1051-4651},
  keyword      = {Visual systems,Gaussian shaped smoothing kernels,Video sequences,Image sequences},
  language     = {eng},
  location     = {Hong Kong, China},
  pages        = {954--959},
  publisher    = {IEEE--Institute of Electrical and Electronics Engineers Inc.},
  title        = {Motion dependent spatiotemporal smoothing for noise reduction in very dim light image sequences},
  url          = {http://dx.doi.org/10.1109/ICPR.2006.813},
  volume       = {3},
  year         = {2006},
}