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Adaptive enhancement and noise reduction in very low light-level video

Malm, Henrik LU ; Oskarsson, Magnus LU ; Warrant, Eric; Clarberg, Petrik LU ; Hasselgren, Jon LU and Lejdfors, Calle LU (2007) IEEE 11th International Conference on Computer Vision, 2007. ICCV 2007 In 11th International Conference on Computer Vision, 2007 p.1395-1402
Abstract
A general methodology for noise reduction and contrast enhancement in very noisy image data with low dynamic range is presented. Video footage recorded in very dim light is especially targeted. Smoothing kernels that automatically adapt to the local spatio-temporal intensity structure in the

image sequences are constructed in order to preserve and enhance fine spatial detail and prevent motion blur. In color image data, the chromaticity is restored and demosaicing of raw RGB input data is performed simultaneously with the noise reduction. The method is very general, contains few user-defined parameters and has been developed for efficient

parallel computation using a GPU. The technique has been applied to image sequences... (More)
A general methodology for noise reduction and contrast enhancement in very noisy image data with low dynamic range is presented. Video footage recorded in very dim light is especially targeted. Smoothing kernels that automatically adapt to the local spatio-temporal intensity structure in the

image sequences are constructed in order to preserve and enhance fine spatial detail and prevent motion blur. In color image data, the chromaticity is restored and demosaicing of raw RGB input data is performed simultaneously with the noise reduction. The method is very general, contains few user-defined parameters and has been developed for efficient

parallel computation using a GPU. The technique has been applied to image sequences with various degrees of darkness and noise levels, and results from some of these tests, and comparisons to other methods, are presented. The present work has been inspired by research on vision in nocturnal

animals, particularly the spatial and temporal visual summation that allows these animals to see in dim light. (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
in
11th International Conference on Computer Vision, 2007
pages
8 pages
publisher
IEEE--Institute of Electrical and Electronics Engineers Inc.
conference name
IEEE 11th International Conference on Computer Vision, 2007. ICCV 2007
external identifiers
  • wos:000255099301052
  • scopus:50649084572
ISSN
1550-5499
ISBN
978-1-4244-1631-8
DOI
10.1109/ICCV.2007.4409007
language
English
LU publication?
yes
id
b7cc324f-0712-42e5-9568-db88bec83a10 (old id 1396719)
date added to LUP
2009-05-15 12:45:48
date last changed
2017-10-22 04:43:59
@inproceedings{b7cc324f-0712-42e5-9568-db88bec83a10,
  abstract     = {A general methodology for noise reduction and contrast enhancement in very noisy image data with low dynamic range is presented. Video footage recorded in very dim light is especially targeted. Smoothing kernels that automatically adapt to the local spatio-temporal intensity structure in the<br/><br>
image sequences are constructed in order to preserve and enhance fine spatial detail and prevent motion blur. In color image data, the chromaticity is restored and demosaicing of raw RGB input data is performed simultaneously with the noise reduction. The method is very general, contains few user-defined parameters and has been developed for efficient<br/><br>
parallel computation using a GPU. The technique has been applied to image sequences with various degrees of darkness and noise levels, and results from some of these tests, and comparisons to other methods, are presented. The present work has been inspired by research on vision in nocturnal<br/><br>
animals, particularly the spatial and temporal visual summation that allows these animals to see in dim light.},
  author       = {Malm, Henrik and Oskarsson, Magnus and Warrant, Eric and Clarberg, Petrik and Hasselgren, Jon and Lejdfors, Calle},
  booktitle    = {11th International Conference on Computer Vision, 2007},
  isbn         = {978-1-4244-1631-8},
  issn         = {1550-5499},
  language     = {eng},
  pages        = {1395--1402},
  publisher    = {IEEE--Institute of Electrical and Electronics Engineers Inc.},
  title        = {Adaptive enhancement and noise reduction in very low light-level video},
  url          = {http://dx.doi.org/10.1109/ICCV.2007.4409007},
  year         = {2007},
}