research-article

PCA based video denoising in a non-local means framework

Authors:

Hemalata Bhujle,

Subhasis ChaudhuriAuthors Info & Claims

ICVGIP '12: Proceedings of the Eighth Indian Conference on Computer Vision, Graphics and Image Processing

Article No.: 64, Pages 1 - 8

https://doi.org/10.1145/2425333.2425397

Published: 16 December 2012 Publication History

Abstract

Nonlocal means (NLM) video denoising algorithm though provide very competitive results, suffer from high computational cost. We propose to reduce the computations through the concept of dimensionality reduction using principle component analysis (PCA). Image neighbourhood representations are projected onto a lower dimensional subspace determined by PCA and weights are computed in this reduced subspace. Principle components are computed globally for an entire video shot having similar frames, which reduces computations drastically. We have used a technique of histogram difference to group the frames with similar visual content. We have achieved an improvement in accuracy in addition to reducing the computation. The proposed method is shown to outperform all other nonlocal means related video denoising methods.

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Cited By

Yamanappa WSudeep PSabu MRajan J(2018)Non-Local Means Image Denoising Using Shapiro-Wilk Similarity MeasureIEEE Access10.1109/ACCESS.2018.28694616(66914-66922)Online publication date: 2018
https://doi.org/10.1109/ACCESS.2018.2869461
Bhujle HBatra DBrown MNatarajan V(2016)Feature-preserving 3D fluorescence image sequence denoisingProceedings of the Tenth Indian Conference on Computer Vision, Graphics and Image Processing10.1145/3009977.3009983(1-8)Online publication date: 18-Dec-2016
https://dl.acm.org/doi/10.1145/3009977.3009983

Index Terms

PCA based video denoising in a non-local means framework
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
  2. Computer graphics
    1. Image manipulation

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Published In

cover image ACM Other conferences

ICVGIP '12: Proceedings of the Eighth Indian Conference on Computer Vision, Graphics and Image Processing

December 2012

633 pages

ISBN:9781450316606

DOI:10.1145/2425333

Program Chairs:
Bill Triggs
CNRS, France
,
Kavita Bala
Cornell University
,
Sharat Chandran
IIT Bombay, India

Copyright © 2012 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 16 December 2012

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ICVGIP '12

ICVGIP '12: The Eighth Indian Conference on Vision, Graphics and Image Processing

December 16 - 19, 2012

Mumbai, India

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Cited By

Yamanappa WSudeep PSabu MRajan J(2018)Non-Local Means Image Denoising Using Shapiro-Wilk Similarity MeasureIEEE Access10.1109/ACCESS.2018.28694616(66914-66922)Online publication date: 2018
https://doi.org/10.1109/ACCESS.2018.2869461
Bhujle HBatra DBrown MNatarajan V(2016)Feature-preserving 3D fluorescence image sequence denoisingProceedings of the Tenth Indian Conference on Computer Vision, Graphics and Image Processing10.1145/3009977.3009983(1-8)Online publication date: 18-Dec-2016
https://dl.acm.org/doi/10.1145/3009977.3009983

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