Gray Medical Image Compression Using Fractal Concepts

Authors

  • Biswajit Senapati  M-Tech Research Scholar, Department of Computer Science and Engineering, Veer Surendra Sai University of Technology, Sambalpur, Odisha, India
  • Sumitra Kisan  Assistant Professor, Department of Computer Science and Engineering, Veer Surendra Sai University of Technology, Sambalpur, Odisha, India
  • Subhra Priyadarshini Biswal  M-Tech Research Scholar, Department of Computer Science and Engineering, Veer Surendra Sai University of Technology, Sambalpur, Odisha, India
  • Anmol Pattanaik  M-Tech Research Scholar, Department of Computer Science and Engineering, Veer Surendra Sai University of Technology, Sambalpur, Odisha, India

Keywords:

Fractal Images, Peak Signal to Noise Ratio, Compression Ratio

Abstract

Digital image processing is now more popular due to high quality of image. In digital image compression is more popular due to providing high compression ratio. In this paper we discussed fractal images compression methods. Medical, industry, animation is used compression methods for extracting information. Because these images are contain huge amount of information. Then it is very difficult to send large amount of information through any physical or communication medium. Therefore we use some techniques for compressing the information. Information is extracted through images. Image may contain any types such as JPGE, PNG and TIFF etc. Here we discussed the image encoding and decoding methods, image types and survey paper. It is shown that some parameters such as Compression ratio (CR), Peak Signal to Nation Ration (PSNR) is calculated and also histogram graph of each image is shown.

References

  1. G.V.Maha Lakshmi, "A Novel Technique of fractal image compression using neural networks for MRI image", International Journal of Innovations & Advancement in Computer Science IJIACS ISSN 2347 – 8616 Volume 6, Issue 2 February 2017.
  2. Aura Conci, and Felipe R. Aquino, "Fractal Coding based on Image Local Fractal Dimension", In Proceedings of Computational & Applied Mathematics, Vol. 24, No. 1, 2005.
  3. Murray H. Loew, Dunling Li, and Raymond L. Pickholtz., "Adaptive PIFS Model in Fractal Image Compression", In Proc. of SPIE, Vol. 2707, 1996.
  4. DietmarSaupe, Meinrad Rombach, and Harald Fischer, "Fuzzy Clustering for Fractal Image Compression with Applications to Digital Angiography‖, In Proceedings the Third European Congress on Intelligent Techniques and Soft Computing EUFIT'95, Aachen, Aug. 1995
  5. M. F. Barnsley, and L. P. Hurd, Fractal Image Compression. AK Peters‖, Wellesley, 1993.
  6. A.E. Jacquin,"Image coding Based on Fractal Theory of Iterated. Contractive Image Transformations", IEEE Transactions on Image Processing, 1992.

IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology

Downloads

Published

2018-04-30

Issue

Volume 3, Issue 3, March-April-2018

Section

Research Articles

License

Copyright (c) IJSRCSEIT

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
Biswajit Senapati, Sumitra Kisan, Subhra Priyadarshini Biswal, Anmol Pattanaik, " Gray Medical Image Compression Using Fractal Concepts" International Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 3, Issue 3, pp.851-854, March-April-2018.