DOI:10.20894/IJWT.
Periodicity: Bi Annual.
Impact Factor:
SJIF:4.78 & GIF:0.428
Submission:Any Time
Publisher: IIR Groups
Language: English
Review Process:
Double Blinded

News and Updates

Author can submit their paper through online submission. Click here

Paper Submission -> Blind Peer Review Process -> Acceptance -> Publication.

On an average time is 3 to 5 days from submission to first decision of manuscripts.

Double blind review and Plagiarism report ensure the originality

IJWT provides online manuscript tracking system.

Every issue of Journal of IJWT is available online from volume 1 issue 1 to the latest published issue with month and year.

Paper Submission:
Any Time
Review process:
One to Two week
Journal Publication:
June / December

IJWT special issue invites the papers from the NATIONAL CONFERENCE, INTERNATIONAL CONFERENCE, SEMINAR conducted by colleges, university, etc. The Group of paper will accept with some concession and will publish in IJWT website. For complete procedure, contact us at admin@iirgroups.org

Paper Template
Copyright Form
Subscription Form
web counter
web counter
Published in:   Vol. 8 Issue 1 Date of Publication:   June 2019

A Study on Image Denoising using Higher Decomposition Method Based on Wavelet Transform

I.Jailingeswari

Page(s):   07-11 ISSN:   2278-2397
DOI:   10.20894/IJWT.104.008.001.003 Publisher:   Integrated Intelligent Research (IIR)

The Wavelet change is in certainty an unbounded arrangement of different changes, contingent upon the legitimacy work utilized for its calculation. Picture generally gets contorted amid securing, preparing and progress. As wavelet change has many preferences over other strategy, for example, best restriction and multiresolution properties. Wavelet change utilized different strategies for picture denoising, for example, Visu Recoil yet this method have hindrance that it deliver over smoothening of picture which causes obscure in the edges. So to defeat such issue we have proposed new strategy by changing the Visu recoil thresholding systems. We have contrasted our proposed strategy and the Visu thresholding strategy on the premise of PSNR esteem for various wavelet families, for example, Haar, Daubechies, Biorthogonal, Symlet and Coiflet.