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Reseach Article

Validation of Image Compression Algorithms using Neural Network

by Nikhilesh Joshi, Tanuja K. Sarode
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 179 - Number 12
Year of Publication: 2018
Authors: Nikhilesh Joshi, Tanuja K. Sarode
10.5120/ijca2018916127

Nikhilesh Joshi, Tanuja K. Sarode . Validation of Image Compression Algorithms using Neural Network. International Journal of Computer Applications. 179, 12 ( Jan 2018), 1-8. DOI=10.5120/ijca2018916127

@article{ 10.5120/ijca2018916127,
author = { Nikhilesh Joshi, Tanuja K. Sarode },
title = { Validation of Image Compression Algorithms using Neural Network },
journal = { International Journal of Computer Applications },
issue_date = { Jan 2018 },
volume = { 179 },
number = { 12 },
month = { Jan },
year = { 2018 },
issn = { 0975-8887 },
pages = { 1-8 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume179/number12/28849-2018916127/ },
doi = { 10.5120/ijca2018916127 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:55:07.784250+05:30
%A Nikhilesh Joshi
%A Tanuja K. Sarode
%T Validation of Image Compression Algorithms using Neural Network
%J International Journal of Computer Applications
%@ 0975-8887
%V 179
%N 12
%P 1-8
%D 2018
%I Foundation of Computer Science (FCS), NY, USA
Abstract

We live in Digital Era where information is generated at rapid space. Images constitute a major part of information. It becomes essential to use image compression techniques in order to reduce storage space and transmission bandwidth. Image compression algorithm can be validated using Neural Network. In this paper various methods of Image compression such as BTC, DCT, DWT are optimized and Validate using neural network. This is achieved by comparing methods based on set of parameters. . The resultant compression metrics are calculated and visual quality of image is analyzed. Neural network implementation is done based on two different methods desired matrix and entropy based method. Experimental analysis shows 60 % reduction in storage space requirement and effective optimization using different methodology.

References
  1. Rafael C. Gonalez, Richard E.Woods “Digital Image Compression” 3rd Edition, Prentice Hall.
  2. E. J.Delp, O R. Mitchelle “ Image Compression using Block truncation Coding” IEEE Transaction Communication 27(9) (1979) 1335-1342
  3. M. D. Lema, O.R . Mitchelle “Absolute Moment Block ytruncation Coding and its Application to Color Images” IEEE Transcaction Communication Vol COM-32, No.10, pp1148-1157 Oct 1984
  4. S.C .Cheng, W.S.Tsai “ Image Compression by moment-preserving edge detection” Pattern Recognition 27 (11) pp.1439- 1449
  5. U.Y Desai, M.M. Muzuki, B.K.P.Horn “Edge and mean based Compression” MIT Artifical Intelligence Laboratory AI Memo No.1584,November 1996.
  6. T.M.Ammarunnishad, V.K Govindan, T.M Abraham ” Improving BTC Image Compression using a Fuzzy Complement Edge operator”Signal Processing Letters, Vol 88. Issue 12 December 2008 pp. 2989-2997
  7. T.M.Ammarunnishad, V.K Govindan, T.M Abraham “ A Fuzzy Complement edge operator “ IEEE proceeding of the Fourteen International Conference on Advance Computing and Communication Mangalore, Karnataka, India December 2006
  8. Aditya Kumar, Pradeep Singh “ Futuristic Algorithm for Gray Scale Image Based on Enhanced Block Truncation Coding” International Journal of Computer Information system Vol 2 No.5 pp 53-60 ,2011
  9. Jaymol Mathews, Madhu S Nair, Liza Jo ” Modified BTC Algorithm for Gray Scale Images Using max-min Quantizer” IEEE Transaction 2013 pp 377-382
  10. Manish Gupta, Dr. Anil Kumar Garg “Analysis of Image Compression Algorithm Using DCT”, International Journal of Engineering Research and Applications ISSN:2248-9662, Vol 2 Issue 1 Jan-Feb2012 pp 515-521
  11. Mahinderpal Singh, Meenakshi Garg “Mixed DWT-DCT Approached Based Image Compression Technique” International Journal of Engineering and Computer Science ISSN:2319-7242, Vol 3 Issue 11 November 2014 pp 9107-9111
  12. Bhavna Sagwan, Mukesh Sharma, Krishan Gupta “RGB based KMB Image Compression Technique” International Conference on Reliability, Optimization and Information Technology Feb 2014
  13. and Applications ISSN:2248-9662, Vol 2 Issue 1 Jan-Feb2012 pp 515-521
  14. Mahinderpal Singh, Meenakshi Garg “Mixed DWT-DCT Approached Based Image Compression Technique” International Journal of Engineering and Computer Science ISSN:2319-7242, Vol 3 Issue 11 November 2014 pp 9107-9111
  15. Bhavna Sagwan, Mukesh Sharma, Krishan Gupta “RGB based KMB Image Compression Technique” International Conference on Reliability, Optimization and Information Technology Feb 2014
  16. M.Singh and M Garg, “Mixed DWT DCT Approached Based Image Compression technique ” International Journal of Engineering and Computer Science ISSN 2319-7242 volume 3 Issue 11 Nov 2014page 9008 -9111.
Index Terms

Computer Science
Information Sciences

Keywords

Image Compression Entropy Block Truncation Coding Discrete Cosine Transform(DCT) Discrete wavelet tranform(DWT Image Quality Metrics Neural Network Back propogation.