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Novel Wavelet Domain Based Adaptive Thresholding Using Bat Algorithm for Image Compression

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Computational Intelligence in Data Mining

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 990))

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Abstract

Image compression is the significant study in the arena of image processing owing to its enormous usages and its ability to reduce the storage prerequisite and communication bandwidth. Thresholding is a kind of image compression in which computational time increases for multilevel thresholding and hence optimization techniques are applied. The quality of reconstructed image is superior when discrete wavelet transform based thresholding is used as compared to when it is not applied. Both particle swarm optimization and fire fly algorithm becomes unstable when the velocity of the particle becomes maximum and when there is no bright firefly in the search space respectively. To overcome the above-mentioned drawbacks bat algorithm based thresholding in frequency domain is proposed. Echolocation is the sort of sonar used by micro-bats. The way they throng their prey, overcoming the hurdles they come across, pinpointing nestling gaps have become the main motivation research in artificial intelligence. With the feature of frequency tuning and having the benefit of automatic zooming, bat algorithm produces superior PSNR values and quality in reconstructed image and also results in fast convergence rate as compared to state of art of optimization techniques.

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Authors and Affiliations

  1. Department of Electronics & Communication Engineering, JNTUH, Hyderabad, Telangana, India

    V. Manohar & T. Satya Savithri

  2. Department of Electronics & Communication Engineering, Anurag College of Engineering, Hyderabad, Telangana, India

    G. Laxminarayana

Authors
  1. V. Manohar
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  2. G. Laxminarayana
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  3. T. Satya Savithri
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Corresponding author

Correspondence to V. Manohar .

Editor information

Editors and Affiliations

  1. Department of Information Technology, Veer Surendra Sai University of Technology, Burla, Sambalpur, Odisha, India

    Himansu Sekhar Behera

  2. Department of Computer Science and Engineering, Sri Sivani College of Engineering, Srikakulam, Andhra Pradesh, India

    Janmenjoy Nayak

  3. Department of Computer Application, Veer Surendra Sai University of Technology, Burla, Sambalpur, Odisha, India

    Bighnaraj Naik

  4. Faculty of Communication Sciences, University of Teramo, Teramo, Italy

    Danilo Pelusi

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Manohar, V., Laxminarayana, G., Satya Savithri, T. (2020). Novel Wavelet Domain Based Adaptive Thresholding Using Bat Algorithm for Image Compression. In: Behera, H., Nayak, J., Naik, B., Pelusi, D. (eds) Computational Intelligence in Data Mining. Advances in Intelligent Systems and Computing, vol 990. Springer, Singapore. https://doi.org/10.1007/978-981-13-8676-3_24

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