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

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Published

2018-04-30

Issue

Section

Research Articles

How to Cite

[1]
Biswajit Senapati, Sumitra Kisan, Subhra Priyadarshini Biswal, Anmol Pattanaik, " Gray Medical Image Compression Using Fractal Concepts, IInternational 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.