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A Novel Color Image Coding Technique Using Improved BTC with k-means Quad Clustering

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Advances in Signal Processing and Intelligent Recognition Systems

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 264))

Abstract

A new approach to color image compression on HSV model with good quality of reconstructed images and better compression ratio using Improved Block Truncation Coding algorithm with k-means Quad Clustering (IBTC-KQ) is proposed in this paper. The RGB plane of the color image is transformed into HSV plane in order to reduce the high degree of correlation between the RGB planes. Each HSV plane is then encoded using IBTC-KQ method. The block sizes are chosen based on the information content of the respective plane. The result of the proposed method is compared with that of other BTC based methods on RGB model and it shows a better performance both in the visual quality and compression ratio. Also the proposed method involves only less number of simple computations when compared with other BTC methods.

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Author information

Authors and Affiliations

  1. Department of Computer Science, University of Kerala, Kariavattom, Thiruvananthapuram, 695581, Kerala, India

    Jayamol Mathews & Madhu S. Nair

  2. Philips Electronics India Ltd, Bangalore, India

    Liza Jo

Authors
  1. Jayamol Mathews
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  2. Madhu S. Nair
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  3. Liza Jo
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Corresponding author

Correspondence to Jayamol Mathews .

Editor information

Editors and Affiliations

  1. Technopark Campus, Indian Institute of Information Technology and Management – Kerala (IIITM-K), Trivandrum, Kerala, India

    Sabu M. Thampi

  2. Center for Computing Research, National Polytechnic Institute, Mexico City, Mexico

    Alexander Gelbukh

  3. Department of Computer Science and Engineering, Indian Institute of Technology, Kharagpur, India

    Jayanta Mukhopadhyay

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© 2014 Springer International Publishing Switzerland

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Mathews, J., Nair, M.S., Jo, L. (2014). A Novel Color Image Coding Technique Using Improved BTC with k-means Quad Clustering. In: Thampi, S., Gelbukh, A., Mukhopadhyay, J. (eds) Advances in Signal Processing and Intelligent Recognition Systems. Advances in Intelligent Systems and Computing, vol 264. Springer, Cham. https://doi.org/10.1007/978-3-319-04960-1_31

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  • DOI: https://doi.org/10.1007/978-3-319-04960-1_31

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-04959-5

  • Online ISBN: 978-3-319-04960-1

  • eBook Packages: EngineeringEngineering (R0)

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