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Noise Reduction in Video Sequences – The State of Art and the Technique for Motion Detection

by Reeja S.r, N. P. Kavya
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 58 - Number 8
Year of Publication: 2012
Authors: Reeja S.r, N. P. Kavya
10.5120/9304-3526

Reeja S.r, N. P. Kavya . Noise Reduction in Video Sequences – The State of Art and the Technique for Motion Detection. International Journal of Computer Applications. 58, 8 ( November 2012), 31-36. DOI=10.5120/9304-3526

@article{ 10.5120/9304-3526,
author = { Reeja S.r, N. P. Kavya },
title = { Noise Reduction in Video Sequences – The State of Art and the Technique for Motion Detection },
journal = { International Journal of Computer Applications },
issue_date = { November 2012 },
volume = { 58 },
number = { 8 },
month = { November },
year = { 2012 },
issn = { 0975-8887 },
pages = { 31-36 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume58/number8/9304-3526/ },
doi = { 10.5120/9304-3526 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:01:57.496407+05:30
%A Reeja S.r
%A N. P. Kavya
%T Noise Reduction in Video Sequences – The State of Art and the Technique for Motion Detection
%J International Journal of Computer Applications
%@ 0975-8887
%V 58
%N 8
%P 31-36
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

This paper provides a detailed state of the art of different video denoising techniques. Most of the video denoising algorithms are done through the motion detection technique. The main goal is to give a survey of various noise reduction techniques for video. Object detection is the first level of video denoising. The first level can be achieved through Motion Detection. This paper explained about the motion estimation and compensation techniques. The different video denoising techniques, motion detection techniques and the noises used are shown through the taxonomy.

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Index Terms

Computer Science
Information Sciences

Keywords

Object tracking frame differencing image and video denoising

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