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Q-Factor Based Modified Adaptable Vector Quantization Techniques for DCT-Based Image Compression and DSP Implementation

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Innovations in Electronics and Communication Engineering

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 33))

Abstract

In the context of multimedia application, image compression is an integral part of image processing, which is a significant constituent in the present world of computation and communication. The work presented here focusses on the design and the selection of modified adaptive vector quantization techniques used in the image compression and its influence on the quality (Q-factor) of the reconstructed image. The proposal also considers and suggests the modifications to two existing methods by providing comparative evaluation. Both experiments have been tested on MATLAB framework and DSP TMS320C6713. The performance metrics used in the proposed designs are MSE, PSNR, CR, bpp, and percentage space saving with respect to variations in quantization levels, starting from 10 to 90. Such suggested implementations prove to provide better off-the-shelf solutions.

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References

  1. Pu IM (2006) Fundamental data compression. ISBN-13:978–0-7506-6310-6, ISBN-10:0-7506-6310-3. British Library Cataloguing in Publication Data and Library of Congress Cataloguing in Publication Data, Butterworth-Heinemann Publications Copyright © 2006

    Google Scholar 

  2. Skodras A, Christopoulos C, Ebrahimi T (2001) The JPEG 2000 still image compression standard. IEEE Signal Process Mag 36–58, Sept 2001

    Google Scholar 

  3. Martínez JM (ed) (2002) The MPEG standard, ISO/MPEG N4674, Overview of the MPEG-7, Standard, Version 6.0, MPEG Requirements Group, Jeju, Mar 2002

    Google Scholar 

  4. Kornblum JD (2008) Defense Cyber Crime Institute, United States, Using JPEG quantization tables to identify imagery processed by software, Digital Investigation S21–S25, 2008 Digital Forensic Research Workshop. Published by Elsevier Ltd. https://doi.org/10.1016/j.diin.2008.05.004

  5. Fu Q, Jiang B, Wang C, Zhou X (2015) A novel deblocking quantization table for luminance component in baseline JPEG. J Comm 10(8):629–637, Aug 2015. https://doi.org/10.12720/jcm.10.8.629-637

  6. Almohammad A, Ghinea G, Hierons RM (2009) JPEG steganography: a performance evaluation of quantization tables, 2009. In: International Conference on Advanced Information Networking and Applications. IEEE Computer Society, pp 471–478, 1550–445X/09, 2009 IEEE. https://doi.org/10.1109/aina.2009.67

  7. Jog SM, Lokhande SD (2009) A DSP implementation of embedded zero tree wavelet (EZW) image CODEC in image compression system. Rev Paper Int J Recent Trends Eng ACEEE 2(4):162–164

    Google Scholar 

  8. DCT based Image Compression, Vision Research and Image Science Laboratory. http://visl.technion.ac.il

  9. Samadani R (2005) Characterizing and estimating block DCT image compression quantization parameters. In: Asilomar Conference on Signals, Systems and Computers, Nov 2005, Pacific Grove, CA, USA ©IEEE

    Google Scholar 

  10. Wu A, Tsang PW (2010) VLSI implementation of computation efficient color image compression scheme based on adaptive decimation for portable device application. J Signal Process Syst 59(3):267–279, June 2010. Kluwer Academic Publishers Hingham, USA

    Google Scholar 

  11. Dixit MM, Kumar P (2010) Comparative analysis of variable quantization DCT and variable rank matrix SVD algorithms for image compression applications. In: IEEE-ICCIC-2010, IEEE-Xplore, pp 908–912, Dec 2010. https://doi.org/10.1109/iccic.2010.5705879

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Acknowledgements

The authors would like to thank the AICTE-RPS Grants (Ref. No.: 8023/RID/RPS-115(Pvt.)/2011–12) for providing financial assistance towards this research work.

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Authors and Affiliations

  1. Department of E&CE, SDMCET, Dharwad, Karnataka, India

    Mahendra M. Dixit & C. Vijaya

Authors
  1. Mahendra M. Dixit
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  2. C. Vijaya
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Corresponding author

Correspondence to Mahendra M. Dixit .

Editor information

Editors and Affiliations

  1. Guru Nanak Institutions, Ibrahimpatnam, Telangana, India

    H. S. Saini

  2. Guru Nanak Institutions Technical Campus, Ibrahimpatnam, Telangana, India

    Ravi Kishore Singh

  3. Department of Electrical and Computer Engineering, Rutgers University, New Brunswick, NJ, USA

    Vishal M. Patel

  4. Department of Electronics and Communication Engineering, Guru Nanak Institutions Technical Campus, Ibrahimpatnam, Telangana, India

    K. Santhi

  5. Research and Development, Guru Nanak Institutions Technical Campus, Ibrahimpatnam, Telangana, India

    S.V. Ranganayakulu

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Dixit, M.M., Vijaya, C. (2019). Q-Factor Based Modified Adaptable Vector Quantization Techniques for DCT-Based Image Compression and DSP Implementation. In: Saini, H., Singh, R., Patel, V., Santhi, K., Ranganayakulu, S. (eds) Innovations in Electronics and Communication Engineering. Lecture Notes in Networks and Systems, vol 33. Springer, Singapore. https://doi.org/10.1007/978-981-10-8204-7_9

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  • DOI: https://doi.org/10.1007/978-981-10-8204-7_9

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-8203-0

  • Online ISBN: 978-981-10-8204-7

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