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Analysis of Optical Flow Algorithms for Denoising

Larsson, Markus LU and Söderström, Louise LU (2015) In Master's Theses in Mathematical Sciences FMA820 20151
Mathematics (Faculty of Technology) and Numerical Analysis
Abstract
When a video sequence is recorded in low-light conditions, the image often become noisy. Standard methods for noise reduction have difficulties with motion. But the interesting parts in a video is often the ones that are moving, for instance a burglar captured in a surveillance video.

One approach for denoising video sequences is to use temporal filtering controlled by optical flow, which describes how pixels move between two image frames. Today, there exists few studies comparing how different optical flow algorithms perform on noisy video sequences. Four different algorithms have been analyzed in the thesis. Moreover, a comparison on how well they can be used to improve the result of a temporal noise filter has been done. The... (More)
When a video sequence is recorded in low-light conditions, the image often become noisy. Standard methods for noise reduction have difficulties with motion. But the interesting parts in a video is often the ones that are moving, for instance a burglar captured in a surveillance video.

One approach for denoising video sequences is to use temporal filtering controlled by optical flow, which describes how pixels move between two image frames. Today, there exists few studies comparing how different optical flow algorithms perform on noisy video sequences. Four different algorithms have been analyzed in the thesis. Moreover, a comparison on how well they can be used to improve the result of a temporal noise filter has been done. The conclusion of the comparison is that optical flow is useful for noise reduction. Algorithms based on patch matching and edge consistency perform better than algorithms based on color consistency.

A recommendation for future work is to combine the best parts of each algorithm to develop a new optical flow algorithm, specialized on noisy image sequences. Furthermore, develop and implement a sophisticated optical flow based noise filter in camera hardware. (Less)
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author
Larsson, Markus LU and Söderström, Louise LU
supervisor
organization
alternative title
Analys av Optiskt Flöde-algoritmer för Brusreducering
course
FMA820 20151
year
type
H2 - Master's Degree (Two Years)
subject
keywords
Optical flow, noise reduction, video sequences, video surveillance, algorithms
publication/series
Master's Theses in Mathematical Sciences
report number
LUTFMA-3275-2015
ISSN
1404-6342
other publication id
2015:E15
language
English
id
5464127
date added to LUP
2015-06-18 12:06:26
date last changed
2015-06-18 12:06:26
@misc{5464127,
  abstract     = {When a video sequence is recorded in low-light conditions, the image often become noisy. Standard methods for noise reduction have difficulties with motion. But the interesting parts in a video is often the ones that are moving, for instance a burglar captured in a surveillance video.

One approach for denoising video sequences is to use temporal filtering controlled by optical flow, which describes how pixels move between two image frames. Today, there exists few studies comparing how different optical flow algorithms perform on noisy video sequences. Four different algorithms have been analyzed in the thesis. Moreover, a comparison on how well they can be used to improve the result of a temporal noise filter has been done. The conclusion of the comparison is that optical flow is useful for noise reduction. Algorithms based on patch matching and edge consistency perform better than algorithms based on color consistency.

A recommendation for future work is to combine the best parts of each algorithm to develop a new optical flow algorithm, specialized on noisy image sequences. Furthermore, develop and implement a sophisticated optical flow based noise filter in camera hardware.},
  author       = {Larsson, Markus and Söderström, Louise},
  issn         = {1404-6342},
  keyword      = {Optical flow,noise reduction,video sequences,video surveillance,algorithms},
  language     = {eng},
  note         = {Student Paper},
  series       = {Master's Theses in Mathematical Sciences},
  title        = {Analysis of Optical Flow Algorithms for Denoising},
  year         = {2015},
}