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Proceedings of Fifth International Conference on Soft Computing for Problem Solving pp 93–104Cite as

Study of Neighborhood Search-Based Fractal Image Encoding

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 436))

Abstract

Fractal image encoding is one of the famous lossy encoding techniques ascertain high compression ratio, higher peak signal-to-noise ratio (PSNR), and good quality of encoded image. Fractal image compression uses the self-similarity property present in the natural image and similarity measure. The main drawback fractal image encoding suffers from is significant time consumption in search of appropriate domain for each range of image blocks. There have been various researches carried out to overcome the limitation of fractal encoding and to speed up the encoder. Initially, various classification and partitioning schemes were used to reduce the search space. A remarkable improvement was made by neighborhood region search strategies, which classify the image blocks on the basis of some feature vectors of image to restrict the region for best matching pair of domain and range, and also reduces the search complexity to logarithmic time. In this paper, three image block preprocessing approaches using neighborhood search method are explained in different domains and all these approaches are compared on the basis of their simulation results.

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Authors and Affiliations

  1. CSE Department, ASET, Amity University, Noida, India

    Indu Aggarwal &  Richa Gupta

Authors
  1. Indu Aggarwal
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  2. Richa Gupta
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Corresponding author

Correspondence to Indu Aggarwal .

Editor information

Editors and Affiliations

  1. Dept of Applied Sci & Eng, Indian Instit of Tech Roorkee, Roorkee, India

    Millie Pant

  2. Department of Mathematics, Indian Inst of Tech Roorkee, Roorkee, India

    Kusum Deep

  3. Chankyapuri, Rm 327, South Asian Univ, Akbar Bhawan, New Delhi, India

    Jagdish Chand Bansal

  4. Department of Mathematics and Comp Sci, Liverpool Hope University, LIVERPOOL, United Kingdom

    Atulya Nagar

  5. Department of Mathematics, National Inst of Tech Silchar, Silchar, Assam, India

    Kedar Nath Das

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© 2016 Springer Science+Business Media Singapore

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Indu Aggarwal, Richa Gupta (2016). Study of Neighborhood Search-Based Fractal Image Encoding. In: Pant, M., Deep, K., Bansal, J., Nagar, A., Das, K. (eds) Proceedings of Fifth International Conference on Soft Computing for Problem Solving. Advances in Intelligent Systems and Computing, vol 436. Springer, Singapore. https://doi.org/10.1007/978-981-10-0448-3_8

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  • DOI: https://doi.org/10.1007/978-981-10-0448-3_8

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-0447-6

  • Online ISBN: 978-981-10-0448-3

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