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

Optimal image compression via block-based adaptive colour reduction with minimal contour effect Multimed Tools Appl https://doi.org/10.1007/s11042-018-6118-y Optimal image compression via block-based adaptive colour reduction with minimal contour effect 1 1 Iiris Lusi ¨ · Anastasia Bolotnikova · 1 2 Morteza Daneshmand · Cagri Ozcinar · 1,3 Gholamreza Anbarjafari Received: 5 July 2017 / Revised: 27 March 2018 / Accepted: 8 May 2018 © Springer Science+Business Media, LLC, part of Springer Nature 2018 Abstract Current image acquisition devices require tremendous amounts of storage for sav- ing 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 compres- sion stage, a methodology taking advantage of block-based singular value decomposition and wavelet difference reduction is adopted. Considering 35000 sample images from vari- ous databases, the proposed method outperforms centre cut, moment-preserving threshold, inter-colour correlation, generic K-means and quantisation by dimensionality http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Multimedia Tools and Applications Springer Journals

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

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Publisher
Springer US
Copyright
Copyright © 2018 by Springer Science+Business Media, LLC, part of Springer Nature
Subject
Computer Science; Multimedia Information Systems; Computer Communication Networks; Data Structures, Cryptology and Information Theory; Special Purpose and Application-Based Systems
ISSN
1380-7501
eISSN
1573-7721
D.O.I.
10.1007/s11042-018-6118-y
Publisher site
See Article on Publisher Site

Abstract

Multimed Tools Appl https://doi.org/10.1007/s11042-018-6118-y Optimal image compression via block-based adaptive colour reduction with minimal contour effect 1 1 Iiris Lusi ¨ · Anastasia Bolotnikova · 1 2 Morteza Daneshmand · Cagri Ozcinar · 1,3 Gholamreza Anbarjafari Received: 5 July 2017 / Revised: 27 March 2018 / Accepted: 8 May 2018 © Springer Science+Business Media, LLC, part of Springer Nature 2018 Abstract Current image acquisition devices require tremendous amounts of storage for sav- ing 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 compres- sion stage, a methodology taking advantage of block-based singular value decomposition and wavelet difference reduction is adopted. Considering 35000 sample images from vari- ous databases, the proposed method outperforms centre cut, moment-preserving threshold, inter-colour correlation, generic K-means and quantisation by dimensionality

Journal

Multimedia Tools and ApplicationsSpringer Journals

Published: Jun 2, 2018

References

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