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Wolf Pack algorithm for a fractal image compression

Published: 22 November 2016 Publication History

Abstract

The fractal image compression is a recent tool for encoding natural images. It builds on the local self-similarities and the generation of copies of blocks based on mathematical transformations. The technique seems interesting in both theory and application but have a drawback renders in real time usage due to the high resource requirement when encoding wide data. By another way, heuristics algorithms represent a set of approaches used to solve hard optimization tasks with rational resources consumption. They are characterized with their fast convergence and reducing of research complexity. The purpose of this paper is to provide, and for a first time, more detailed study about the Wolf Pack Algorithm for the fractal image compression. The performed experiments showed its effectiveness in the resolution of such problem. Moreover, a brief comparison with the exhaustive search establishes this advantage.

References

[1]
Galabov M. Fractal image compression. Proc 4th Int Conf Conf Comput Syst Technol e- Learning - CompSysTech '03 [Internet]. 2003;43(6):320--6. Available from:http://www.ams.org/notices/199606/barnsley.pdf\npapers2://publication/uuid/46C34B7 0-A7F6-4C48-81E82B137CC59519\nhttp://portal.acm.org/citation.cfm?doid=973620.973673
[2]
Thanushkodi KG, Bhavani S. Comparison of fractal coding methods for medical image compression. IET Image Process [Internet]. 2013;7(7):686--93. Available from: http://digitallibrary.theiet.org/content/journals/10.1049/iet-ipr.2012.0041
[3]
Selim A, Hadhoud MM, Salem OM. A comparison study between spiral and traditional fractal image compression. In: Proceedings - The 2009 International Conference on Computer Engineering and Systems, ICCES'09. 2009. p. 39--44.
[4]
Jeng JH, Tseng CC, Hsieh JG. Study on Huber fractal image compression. IEEE Trans Image Process. 2009;18(5):995--1003.
[5]
Li J, Kuo CCJ. Image compression with a hybrid wavelet-fractal coder. IEEE Trans Image Process. 1999;8(6):868--74.
[6]
Han JHJ. Fast Fractal Image Compression Using Fuzzy Classification. 2008 Fifth Int Conf Fuzzy Syst Knowl Discov. 2008;3:272--6.
[7]
Mitra SK, Murthy C a, Kundu MK. Technique for fractal image compression using genetic algorithm. IEEE Trans Image Process. 1998;7(4):586--93.
[8]
Li J, Yuan D, Xie Q, Zhang C. Fractal Image Compression by Ant Colony Algorithm. In: 2008 The 9th International Conference for Young Computer Scientists [Internet]. 2008. p. 1890--4. Available from: http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=4709262
[9]
Tseng C-C, Hsieh J-G, Jeng J-H. Fractal image compression using visual-based particle swarm optimization. Image Vis Comput [Internet]. 2008;26(8):1154--62. Available from: http://www.sciencedirect.com/science/article/pii/S026288560800022X
[10]
Olamaei J, Niknam T, Gharehpetian G. Application of particle swarm optimization for distribution feeder reconfiguration considering distributed generators. Appl Math Comput. 2008;201(1-2):575--86.
[11]
Gandomi AH, Alavi AH. Multi-stage genetic programming: A new strategy to nonlinear system modeling. Inf Sci (Ny) [Internet]. 2011;181(23):5227--39. Available from: http://linkinghub.elsevier.com/retrieve/pii/S0020025511003586
[12]
Blum C, Li X. Swarm Intelligence in Optimization. Swarm Intell Introd Appl. 2008;43--85.
[13]
Felix TSC, Manoj KT. Swarm Intelligence, Focus on Ant and Particle Swarm Optimization. In: Felix TSC, Manoj KT, editors. Numerical Analysis and Scientific Computing. I-Tech Education and Publishing; 2007.
[14]
Wu HS, Zhang FM. Wolf pack algorithm for unconstrained global optimization. Math Probl Eng. 2014;2014.
[15]
Lu G. Fractal image compression. Signal Process Image Commun. 1993;5(4):327--43.
[16]
Hutchinson J. Fractals and self-similarity. Indiana Univ Math J. 1981;30(5):713--47.
[17]
Barnsley MF, Demko S. Iterated Function Systems and the Global Construction of Fractals. Proc R Soc A Math Phys Eng Sci [Internet]. 1985;399(1817):243--75. Available from:
[18]
Peitgen H-O, Jürgens H, Saupe D. Chaos and Fractals [Internet]. Mathematica. 2004. 920 p. Available from: http://www.amazon.ca/exec/obidos/redirect?tag=citeulike0920&path=ASIN/0387202293.
[19]
??ien GE, Leps??y S. Fractal-based image coding with fast decoder convergence. Signal Processing. 1994;40(1):105--17.
[20]
Ho Moon Y, Soon Kim H, Shin Kim Y, Ho Kim J. A novel fast fractal decoding algorithm. Signal Process Image Commun [Internet]. 1999;14(4):325--33. Available from: http://www.sciencedirect.com/science/article/pii/S0923596598000162\nhttp://www.sciencedirect.com/science/article/pii/S0923596598000162/pdfft?md5=a3409e9cff1f4eb70a5e7479959c170d&pid=1-s2.0-S0923596598000162-main.pdf
[21]
Moon YH, Baek KR, Kim YS, Kim JH. Fast fractal decoding algorithm with convergence criteria. Opt Eng. 1997;36(7):1992--9.
[22]
Jacquin AE. Image Coding Based on a Fractal Theory of Iterated Contractive Image Transformations. IEEE Trans Image Process. 1992;1(1):18--30.
[23]
Jacquin AE. Fractal image coding: a review. G06T9/00F [Internet]. 1993;81(10):1451--65. Available from: http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=241507
[24]
Thomas L, Deravi F. Region-based fractal image compression using heuristic search. Image Process IEEE Trans. 1995;4(6):832--8.
[25]
Cardinal J. Fast fractal compression of greyscale images. IEEE Trans Image Process. 2001;10(1):159--64.
[26]
He C, Xu X, Yang J. Fast fractal image encoding using onenorm of normalised block. Chaos, Solitons and Fractals. 2006;27(5):1178--86.
[27]
Tong CS, Pi M. Fast fractal image encoding based on adaptive search. IEEE Trans Image Process. 2001;10(9):1269--77.
[28]
Hartenstein H, Saupe D. Lossless acceleration of fractal image encoding via the fast Fourier transform. Signal Process Image Commun. 2000;16(4):383--94.
[29]
Zhang C, Zhou Y, Zhang Z. Fast Fractal Image Encoding Based on Special Image Features. Tsinghua Sci Technol. 2007;12(1):58--62.
[30]
Truong TK, Jeng JH, Reed IS, Lee PC, Li AQ. A fast encoding algorithm for fractal image compression using the DCT inner product. IEEE Trans Image Process. 2000;9(4):529--35.
[31]
Lin YL, Wu MS. An edge property-based neighborhood region search strategy for fractal image compression. Comput Math with Appl. 2011;62(1):310--8

Cited By

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  • (2017)A chaos wolf optimization algorithm with self-adaptive variable step-sizeAIP Advances10.1063/1.50051307:10(105024)Online publication date: Oct-2017

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cover image ACM Other conferences
MedPRAI-2016: Proceedings of the Mediterranean Conference on Pattern Recognition and Artificial Intelligence
November 2016
163 pages
ISBN:9781450348768
DOI:10.1145/3038884
  • General Chairs:
  • Chawki Djeddi,
  • Imran Siddiqi,
  • Akram Bennour,
  • Program Chairs:
  • Youcef Chibani,
  • Haikal El Abed
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 22 November 2016

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  1. Fractal image compression
  2. bio-inspired heuristics
  3. wolf pack algorithm

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  • (2017)A chaos wolf optimization algorithm with self-adaptive variable step-sizeAIP Advances10.1063/1.50051307:10(105024)Online publication date: Oct-2017

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