Removal of Noise from Video Signals using Adaptive Temporal Averaging

Himanshu Makkar

Removal of Noise from Video Signals using Adaptive Temporal Averaging

Himanshu Makkar * §

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Suresh Gyan Vihar University Jaipur

Removal of Noise from Video Signals using Adaptive Temporal Averaging

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Abstract

This abstract proposed an algorithm for video denoising base on adaptive, pixel-wise, temporal averaging. This algorithm decomposes video signals into the set of 1-D time dependent signals and then removes the noise via establish the temporal averaging intervals during each signal from the set. Temporal averaging intervals established by simple, effective evaluation process which contain two-way thresholding. The proposed algorithm is experienced on quite a few types of 1-D signals and benchmark videos. Experiments advise that the proposed algorithm, regardless of its ease, produces high-quality denoising results.

References

11 Cites in Article

Reference Format

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Funding

No external funding was declared for this work.

Conflict of Interest

The authors declare no conflict of interest.

Ethical Approval

No ethics committee approval was required for this article type.

Data Availability

Not applicable for this article.

How to Cite This Article

Himanshu Makkar. 2018. "Removal of Noise from Video Signals using Adaptive Temporal Averaging". Global Journal of Research in Engineering - F: Electrical & Electronic GJRE-F Volume 17 (GJRE Volume 17 Issue F8).

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GJRE Volume 17 Issue F8

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Journal Specifications

Crossref Journal DOI 10.17406/gjre

Print ISSN 0975-5861

e-ISSN 2249-4596

Keywords

Not Found

Classification

GJRE-F Classification FOR Code: 090609

Submission ReceivedDecember 10, 2016
Peer Review Double Blind
Handling Editor
Accepted January 5, 2017
Published January 15, 2017

Version of record

v1.2

Issue date

January 29, 2018

Language

English

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Article Matrices

Total Score: 102

Country: India

Subject: Global Journal of Research in Engineering

Authors: Himanshu Makkar, Prof. Onkar Singh Lamba (PhD/Dr. count: 0)

View Count (all-time): 387

Total Views (Real + Logic): 1430

Total Downloads (simulated): 104

Publish Date: 2017 01, Sun

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Total Views: 1.4K

Total Downloads: 104

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