Open Access   Article Go Back

Fractal Image Compression Techniques

Nitu 1 , Yogesh Kumar2 , Rahul Rishi3

Section:Research Paper, Product Type: Journal Paper
Volume-7 , Issue-1 , Page no. 229-233, Jan-2019

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v7i1.229233

Online published on Jan 31, 2019

Copyright © Nitu, Yogesh Kumar, Rahul Rishi . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

View this paper at   Google Scholar | DPI Digital Library

XML View
PDF Download

How to Cite this Paper

  • IEEE Citation
  • MLA Citation
  • APA Citation
  • BibTex Citation
  • RIS Citation

IEEE Style Citation: Nitu, Yogesh Kumar, Rahul Rishi, “Fractal Image Compression Techniques,” International Journal of Computer Sciences and Engineering, Vol.7, Issue.1, pp.229-233, 2019.

MLA Style Citation: Nitu, Yogesh Kumar, Rahul Rishi "Fractal Image Compression Techniques." International Journal of Computer Sciences and Engineering 7.1 (2019): 229-233.

APA Style Citation: Nitu, Yogesh Kumar, Rahul Rishi, (2019). Fractal Image Compression Techniques. International Journal of Computer Sciences and Engineering, 7(1), 229-233.

BibTex Style Citation:
@article{Kumar_2019,
author = {Nitu, Yogesh Kumar, Rahul Rishi},
title = {Fractal Image Compression Techniques},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {1 2019},
volume = {7},
Issue = {1},
month = {1},
year = {2019},
issn = {2347-2693},
pages = {229-233},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=3489},
doi = {https://doi.org/10.26438/ijcse/v7i1.229233}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v7i1.229233}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=3489
TI - Fractal Image Compression Techniques
T2 - International Journal of Computer Sciences and Engineering
AU - Nitu, Yogesh Kumar, Rahul Rishi
PY - 2019
DA - 2019/01/31
PB - IJCSE, Indore, INDIA
SP - 229-233
IS - 1
VL - 7
SN - 2347-2693
ER -

VIEWS PDF XML
466 340 downloads 228 downloads
  
  
           

Abstract

Digital image are used in several areas. Digital image includes large amount of data. So transmission of such large amount of data require large storage space. Hence to deal which such problems, image compression is used. Image compression is a technique in which redundant information of image is removed, such that only essential information remain. Image compression technique is also helpful in reduce storage size, transmission bandwidth and transmission time. This paper provides review and comparison of different image compression techniques like DCT ( Discrete Cosine Transform ) , DWT ( Discrete Wavelet Transform) and Hybrid (DCT and DWT) and Fractal Image compression by using Affine Transformation and Iterated function system ( FIS). Research finding of this paper helps to build new and more effective image compression technique.

Key-Words / Index Term

DCT (Discrete Cosine Transform), DWT (Discrete Wavelet Transform), Fractal image compression (FIC), Affine Transformation, Iterated function system (FIS)

References

[1] A Jain, “Fundamental of digital image processing” Prentice Hall, 1989.
[2]M. Rabbani and P. Jones , “Digital Image compression techniques”, PIE opt. Eng. Press, Bellingham , Washington , Tech Rep, 1991.
[3]A Lewis and G. Knowles – “Image compression using the 2- D wavelet transform” IEEE Trans Image Processing vol.1 pp. 244- 250 , April 1992.
[4] Dan Liu , Peter K , Jimack, “A survey of parallel Algorithm for fractal image compression” P.No. 1-15, 2007.
[5]Chong Fu and Zhiliang Zhu , “A DCT based fractal image compression method” International Conference IEEE paper , 2009.
[6]Aree Ali Mohammed, Janal Ali Hussein ,“ Hybrid transform coding schemes for Medical Image Application”, 2011.
[7]Er. RamandeepKaur ,Navneet Randhawa ,“Image compression using DCT and DWT” 2012.
[8]A.G. Ananth and Veenadevi S. V ,“ Fractal Image compression Using Quadtree decomposition and Huffman Coding”, Signal and Image processingAn International Journal ( SIPIJ) Vol. 3 No. 2 April 2012.
[9] Dr. SophinSeelil , Dr. M. K. Jeya Kumar , “ A Study on fractal image compression using soft Computing techniques” IJCSI ( International Journal of computer Science Issues ), Vol. 9 Issue 6, No. 2, November 2012 , P. No. 420 – 430.
[10]Manjinder Kaur ,Gagan preetkaur ,“ Survey of lossless and losy Image compression Techniques” , 2013.
[11]Rasha Adel Ibrahim et. Al , “An Enchnaced Fractal Image Compression Integration Quantized Quadtree and Entropy Coding” IEEE 2015.
[12]Utpal Nandi and Jyotsna Kumar Mandal et .al ,“ Fractal Image Compression with Quadtree Partitioning and a new fast classification strategy” International Conference IEEE paper 2015 .
[13]Sonali V. Kolekar and Prof .PrachiSorte ,“ An Efficient and Secure fractal image and video compression” International Journal of Innovative Research in computer and Communication Engineering , vol. 4 , Issue 12 , December 2016 , P.No. 1-6 .
[14]Sunwoong Kim , Hyuk – Jae Lee , “RGBW image compression by low complexity adaptive multilevel block truncating coding” , Volume 62 , P. No. 412 - 419 , 2016.
[15] Ryan Rey M. Daga , “Improved K-d Tree segmented block truncate coding for color image compression” , IEEE 2nd International Conference on signal and Image processing ( ICSIP), Pages 178 – 182 . 2017.