Adaptive enhancement and noise reduction in very low light-level video
Malm, Henrik LU ; Oskarsson, Magnus LU
; Warrant, Eric
LU
; Clarberg, Petrik
LU
; Hasselgren, Jon
LU
and Lejdfors, Calle
LU
(2007)
IEEE 11th International Conference on Computer Vision, 2007. ICCV 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:
https://lup.lub.lu.se/record/1396719
- author
- Malm, Henrik
LU
; Oskarsson, Magnus
LU
; Warrant, Eric
LU
; Clarberg, Petrik
LU
; Hasselgren, Jon
LU
and Lejdfors, Calle
LU
- organization
- publishing date
- 2007
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- host publication
- 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
- conference location
- Rio de Janeiro, Brazil
- conference dates
- 2007-10-14 - 2007-10-21
- 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
- additional info
- The information about affiliations in this record was updated in December 2015. The record was previously connected to the following departments: Mathematics (Faculty of Technology) (011015005), Zoology (Closed 2011) (011012000), Computer Science (011014004)
- id
- b7cc324f-0712-42e5-9568-db88bec83a10 (old id 1396719)
- date added to LUP
- 2016-04-01 16:41:25
- date last changed
- 2024-02-15 13:47:16
@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}},
doi = {{10.1109/ICCV.2007.4409007}},
year = {{2007}},
}