DOI:10.20894/IJDMTA.
Periodicity: Bi Annual.
Impact Factor:
SJIF:4.893 & GIF:0.787
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

IJDMTA provides online manuscript tracking system.

Every issue of Journal of IJDMTA 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

IJDMTA 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 IJDMTA website. For complete procedure, contact us at admin@iirgroups.org
Paper Template
Copyright Form
Subscription Form
web counter
web counter
Published in:   Vol. 4 Issue 1 Date of Publication:   June 2015

Compression of an image using Wavelet Transformation with Unsupervised Learning Approach

A.J.Rajeswari Joe,N. Rama

Page(s):   40-42 ISSN:   2278-2397
DOI:   10.20894/IJDMTA.102.004.001.010 Publisher:   Integrated Intelligent Research (IIR)

Image compression is a demanding research area in the field of visual communication, in entertainment, medical and business applications. A new method is proposed using unsupervised learning neural networks and wavelet transformations, since the wavelet transformation uses subband decomposition of an image, it provides enhanced picture quality at higher compression ratios, Also our new algorithm avoids blocking artifacts. In this paper, the performances of haar and DB2 wavelet family are compared with MSE and PSNR. The experiment was carried out with .jpeg images. It is a good reference for application developers to select a good wavelet transformation system.