Next Article in Journal
The Singularities Near the Corner of a Viscoelastic Fluid in a 2D Cavity
Previous Article in Journal
Investigation of the Stresses and Strains of Steel Column-Beam Connections Subjected to Seismic Loading
Article Menu

Article Versions

Export Article

Open AccessArticle
Math. Comput. Appl. 1996, 1(1), 165-171; doi:10.3390/mca1010165

Comparing Artificial Neural Networks (ANN) Image Compression Technique with Different Image Compression Techniques

Celal Bayar U., Electric-Eleetronic Eng. Dep., Manisa, Turkey
*
Author to whom correspondence should be addressed.
Published: 1 June 1996
Download PDF [3737 KB, uploaded 1 April 2016]

Abstract

In this paper it is presented that, 256 × 256 16 gray level images can be compressed fast and efficiently by using neural networks . Compression results were compared with the other methods according to mean square error (MSE) and visual of the image and it is seen that by further works on ANN the images can be compressed better.
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

Karlık, B.; Aydın, S.; Kılıç, İ. Comparing Artificial Neural Networks (ANN) Image Compression Technique with Different Image Compression Techniques. Math. Comput. Appl. 1996, 1, 165-171.

Show more citation formats Show less citations formats

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Math. Comput. Appl. EISSN 2297-8747 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top