Skip to main content
SpringerLink
Log in

JPEG Quantization Table Optimization by Guided Fireworks Algorithm

  • Conference paper
  • First Online:
Combinatorial Image Analysis (IWCIA 2017)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 10256))

Included in the following conference series:

Abstract

Digital images are very useful and ubiquitous, however there is a problem with their storage because of their large size and memory requirement. JPEG lossy compression algorithm is prevailing standard that solves that problem. It facilitates different levels of compression (and the corresponding quality) by using recommended quantization tables. It is possible to optimize these tables for better image quality at the same level of compression. This presents a hard combinatorial optimization problem for which stochastic metaheuristics proved to be efficient. In this paper we propose an adjustment of the recent guided fireworks algorithm from the class of swarm intelligence algorithms for quantization table optimization. We tested the proposed approach on standard benchmark images and compared results with other approaches from literature. By using various image similarity metrics our approach proved to be more successful.

M. Tuba was supported by the Ministry of Education, Science and Technological Development of Republic of Serbia, Grant no. III-44006.

D. Simian was supported by the research grant LBUS-IRG-2015-01, project financed by Lucian Blaga University of Sibiu.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Alam, L., Dhar, P.K., Hasan, M.A.R., Bhuyan, M.G.S., Daiyan, G.M.: An improved JPEG image compression algorithm by modifying luminance quantization table. Int. J. Comput. Sci. Netw. Secur. (IJCSNS) 17(1), 200 (2017)

    Google Scholar 

  2. Alihodzic, A., Tuba, M.: Improved bat algorithm applied to multilevel image thresholding. Sci. World J. 2014, 1–17 (2014)

    Article  Google Scholar 

  3. Aschwanden, M.J.: Image processing techniques and feature recognition in solar physics. Sol. Phys. 262(2), 235–275 (2010)

    Article  Google Scholar 

  4. Bacanin, N., Tuba, M.: Firefly algorithm for cardinality constrained mean-variance portfolio optimization problem with entropy diversity constraint. Sci. World J. 2014, 1–16 (2014)

    Article  Google Scholar 

  5. Chao, J., Chen, H., Steinbach, E.: On the design of a novel JPEG quantization table for improved feature detection performance. In: IEEE International Conference on Image Processing, pp. 1675–1679 (2013)

    Google Scholar 

  6. Dorigo, M., Gambardella, L.M.: Ant colonies for the travelling salesman problem. Biosystems 43(2), 73–81 (1997)

    Article  Google Scholar 

  7. Dua, R.L., Gupta, N.: Fast color image quantization based on bacterial foraging optimization. In: Fourth International Conference on Advances in Recent Technologies in Communication and Computing (ARTCom), pp. 100–102 (2012)

    Google Scholar 

  8. Duan, L.Y., Liu, X., Chen, J., Huang, T., Gao, W.: Optimizing JPEG quantization table for low bit rate mobile visual search. In: Visual Communications and Image Processing, pp. 1–6 (2012)

    Google Scholar 

  9. Ernawan, F., Nugraini, S.H.: The optimal quantization matrices for JPEG image compression from psychovisual threshold. J. Theor. Appl. Inform. Technol. 70(3), 566–572 (2014)

    Google Scholar 

  10. Gunda, N.S.K., Choi, H.W., Berson, A., Kenney, B., Karan, K., Pharoah, J.G., Mitra, S.K.: Focused ion beam-scanning electron microscopy on solid-oxide fuel-cell electrode: Image analysis and computing effective transport properties. J. Power Sources 196(7), 3592–3603 (2011)

    Article  Google Scholar 

  11. Gupta, M., Garg, A.K.: Analysis of image compression algorithm using DCT. Int. J. Eng. Res. Appl. (IJERA) 2(1), 515–521 (2012)

    Google Scholar 

  12. He, W., Mi, G., Tan, Y.: Parameter optimization of local-concentration model for spam detection by using fireworks algorithm. In: Tan, Y., Shi, Y., Mo, H. (eds.) ICSI 2013. LNCS, vol. 7928, pp. 439–450. Springer, Heidelberg (2013). doi:10.1007/978-3-642-38703-6_52

    Chapter  Google Scholar 

  13. Jiang, C., Pang, Y., Xiong, S.: A high capacity steganographic method based on quantization table modification and F5 algorithm. Circuits Syst. Sig. Process. 33(5), 1611–1626 (2014)

    Article  Google Scholar 

  14. Karaboga, D.: An idea based on honey bee swarm for numerical optimization. Technical report - TR06, pp. 1–10 (2005)

    Google Scholar 

  15. Kumar, B.V., Karpagam, M.: Differential evolution versus genetic algorithm in optimising the quantisation table for JPEG baseline algorithm. Int. J. Adv. Intell. Paradigms 7(2), 111–135 (2015)

    Article  Google Scholar 

  16. Lazzerini, B., Marcelloni, F., Vecchio, M.: A multi-objective evolutionary approach to image quality/compression trade-off in JPEG baseline algorithm. Appl. Soft Comput. 10(2), 548–561 (2010)

    Article  Google Scholar 

  17. Li, J., Tan, Y.: Enhancing interaction in the fireworks algorithm by dynamic resource allocation and fitness-based crowdedness-avoiding strategy. In: IEEE Congress on Evolutionary Computation (CEC), pp. 4015–4021 (2016)

    Google Scholar 

  18. Li, J., Zheng, S., Tan, Y.: The effect of information utilization: Introducing a novel guiding spark in the fireworks algorithm. IEEE Trans. Evol. Comput. 21(1), 153–166 (2017)

    Article  Google Scholar 

  19. Ma, H., Zhang, Q.: Research on cultural-based multi-objective particle swarm optimization in image compression quality assessment. Optik-Int. J. Light and Electron. Opt. 124(10), 957–961 (2013)

    Article  Google Scholar 

  20. Naresh, S., Kumar, B.V., Karpagam, G.: A literature review on quantization table design for the JPEG baseline algorithm. Int. J. Eng. Comput. Sci. 4(10), 14686–14691 (2015)

    Google Scholar 

  21. Starosolski, R.: New simple and efficient color space transformations for lossless image compression. J. Vis. Commun. Image Represent. 25(5), 1056–1063 (2014)

    Article  Google Scholar 

  22. Subotic, M., Tuba, M., Stanarevic, N.: Parallelization of the artificial bee colony (ABC) algorithm. In: Proceedings of the 11th WSEAS International Conference on Evolutionary Computing, vol. 10, pp. 191–196 (2010)

    Google Scholar 

  23. Tan, Y., Zhu, Y.: Fireworks algorithm for optimization. In: Tan, Y., Shi, Y., Tan, K.C. (eds.) ICSI 2010. LNCS, vol. 6145, pp. 355–364. Springer, Heidelberg (2010). doi:10.1007/978-3-642-13495-1_44

    Chapter  Google Scholar 

  24. Thai, T.H., Cogranne, R., Retraint, F., et al.: JPEG quantization step estimation and its applications to digital image forensics. IEEE Trans. Inf. Forensics Secur. 12(1), 123–133 (2017)

    Article  Google Scholar 

  25. Tuba, E., Tuba, M., Beko, M.: Support vector machine parameters optimization by enhanced fireworks algorithm. In: Tan, Y., Shi, Y., Niu, B. (eds.) ICSI 2016. LNCS, vol. 9712, pp. 526–534. Springer, Cham (2016). doi:10.1007/978-3-319-41000-5_52

    Google Scholar 

  26. Tuba, M., Bacanin, N.: Improved seeker optimization algorithm hybridized with firefly algorithm for constrained optimization problems. Neurocomputing 143, 197–207 (2014)

    Article  Google Scholar 

  27. Tuba, M., Bacanin, N.: JPEG quantization tables selection by the firefly algorithm. In: International Conference on Multimedia Computing and Systems (ICMCS), pp. 153–158. IEEE (2014)

    Google Scholar 

  28. Tuba, M., Bacanin, N., Stanarevic, N.: Guided artificial bee colony algorithm. In: Proceedings of the 5th European Conference on European Computing Conference, pp. 398–403 (2011)

    Google Scholar 

  29. Viswajaa, S., Kumar, V., Karpagam, G.R.: A survey on nature inspired meta-heuristics algorithm in optimizing the quantization table for JPEG baseline algorithm. Int. Adv. Res. J. Sci. Eng. Technol. 2(4), 114–123 (2015)

    Google Scholar 

  30. Yang, X.-S.: Firefly algorithms for multimodal optimization. In: Watanabe, O., Zeugmann, T. (eds.) SAGA 2009. LNCS, vol. 5792, pp. 169–178. Springer, Heidelberg (2009). doi:10.1007/978-3-642-04944-6_14

    Chapter  Google Scholar 

  31. Zheng, S., Janecek, A., Tan, Y.: Enhanced fireworks algorithm. In: 2013 IEEE Congress on Evolutionary Computation, pp. 2069–2077 (2013)

    Google Scholar 

  32. Zheng, S., Li, J., Janecek, A., Tan, Y.: A cooperative framework for fireworks algorithm. IEEE/ACM Trans. Comput. Biol. Bioinform. PP(99), 1 (2016)

    Google Scholar 

  33. Zimbico, A., Schneider, F., Maia, J.: Comparative study of the performance of the JPEG algorithm using optimized quantization matrices for ultrasound image compression. In: 5th ISSNIP-IEEE Biosignals and Biorobotics Conference: Biosignals and Robotics for Better and Safer Living (BRC), pp. 1–6 (2014)

    Google Scholar 

Download references

Acknowledgement

M. Tuba was supported for this research by the Ministry of Education, Science and Technological Development of Republic of Serbia, Grant No. III-44006.

Author information

Authors and Affiliations

  1. Faculty of Mathematics, University of Belgrade, Belgrade, Serbia

    Eva Tuba

  2. Graduate School of Computer Science, John Naisbitt University, Belgrade, Serbia

    Milan Tuba

  3. Faculty of Science, Lucian Blaga University, Sibiu, Romania

    Dana Simian

  4. Qatar Environment and Energy Research Institute, Hamad Bin Khalifa University, Doha, Qatar

    Raka Jovanovic

Authors
  1. Eva Tuba
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Milan Tuba
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Dana Simian
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Raka Jovanovic
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Milan Tuba .

Editor information

Editors and Affiliations

  1. SUNY Buffalo State, Buffalo, New York, USA

    Valentin E. Brimkov

  2. Department of Applied Professional Studies, SUNY Fredonia, Fredonia, New York, USA

    Reneta P. Barneva

Rights and permissions

Reprints and permissions

Copyright information

© 2017 Springer International Publishing AG

About this paper

Cite this paper

Tuba, E., Tuba, M., Simian, D., Jovanovic, R. (2017). JPEG Quantization Table Optimization by Guided Fireworks Algorithm. In: Brimkov, V., Barneva, R. (eds) Combinatorial Image Analysis. IWCIA 2017. Lecture Notes in Computer Science(), vol 10256. Springer, Cham. https://doi.org/10.1007/978-3-319-59108-7_23

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-59108-7_23

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-59107-0

  • Online ISBN: 978-3-319-59108-7

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation