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Multimedia Tools and Applications

, Volume 77, Issue 23, pp 30939–30968 | Cite as

Optimal image compression via block-based adaptive colour reduction with minimal contour effect

  • Iiris Lüsi
  • Anastasia Bolotnikova
  • Morteza Daneshmand
  • Cagri Ozcinar
  • Gholamreza Anbarjafari
Article
  • 128 Downloads

Abstract

Current image acquisition devices require tremendous amounts of storage for saving the data returned. This paper overcomes the latter drawback through proposing a colour reduction technique which first subdivides the image into patches, and then makes use of fuzzy c-means and fuzzy-logic-based inference systems, in order to cluster and reduce the number of the unique colours present in each patch, iteratively. The colours available in each patch are quantised, and the emergence of false edges is checked for, by means of the Sobel edge detection algorithm, so as to minimise the contour effect. At the compression stage, a methodology taking advantage of block-based singular value decomposition and wavelet difference reduction is adopted. Considering 35000 sample images from various databases, the proposed method outperforms centre cut, moment-preserving threshold, inter-colour correlation, generic K-means and quantisation by dimensionality reduction.

Keywords

Adaptive colour reduction Image compression Block processing Colour image processing 

Notes

Acknowledgments

This work has been partially supported by Estonian Research Council Grant PUT638, the Estonian Research Council Grant (PUT638), The Scientific and Technological Research Council of Turkey (TÜBITAK) 1001 Project (116E097), and the Estonian Centre of Excellence in IT (EXCITE) funded by the European Regional Development Fund. The authors would like to thank the RoboCup SPL Team of University of Tartu, Philosopher, for helping to conduct real-time experiments and also gratefully acknowledge the support of NVIDIA Corporation with the donation of the Titan X Pascal GPU.

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Authors and Affiliations

  1. 1.iCV Research Group, Institute of TechnologyUniversity of TartuTartuEstonia
  2. 2.School of Computer Science and StatisticsTrinity College DublinDublin 2Ireland
  3. 3.Department of Electrical and Electronic EngineeringHasan Kalyoncu UniversityGaziantepTurkey

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