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

  • Mahendra M. DixitEmail author
  • C. Vijaya
Conference paper
Part of the Lecture Notes in Networks and Systems book series (LNNS, volume 33)


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.


Image compression DCT Q-factor Quantization DSP 



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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Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  1. 1.Department of E&CESDMCETDharwadIndia

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