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A Novel Hybrid Compression Algorithm for Remote Sensing Imagery

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Proceedings of International Conference on Intelligent Vision and Computing (ICIVC 2022) (ICIVC 2022)

Part of the book series: Proceedings in Adaptation, Learning and Optimization ((PALO,volume 17))

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Abstract

The remote sensing images that are captured by satellites are very high in resolution and involve an enormous amount of memory for storage. These images must be compressed so that more images can be transmitted in the same bandwidth. Extensive study has taken place in the field of compression for remote sensing imagery. In this paper, a novel hybrid algorithm is proposed that increases the compression ratio while maintaining the quality of the image. This hybrid methodology comprises wavelet transform, Run-length, and Arithmetic coding to achieve higher PSNR with minimal MSE. The experimental results up to three levels of wavelet decomposition indicate the range of the obtained parameter values like compression ratio, PSNR, and MSE. The compression is implemented by MATLAB software tool.

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Authors and Affiliations

  1. Department of ECE, SoET, CMR University, Bengaluru, India

    Swetha Vura

  2. VTU, Belagavi, India

    Swetha Vura

  3. Department of TCE, Dr. Ambedkar Institute of Technology, Bengaluru, India

    C. R. Yamuna Devi

Authors
  1. Swetha Vura
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  2. C. R. Yamuna Devi
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Corresponding author

Correspondence to Swetha Vura .

Editor information

Editors and Affiliations

  1. Computer Science and Engineering, Rajasthan Technical University, Kota, Rajasthan, India

    Harish Sharma

  2. Department of Mathematics, National Institute of Technology Agartala, Agartala, Tripura, India

    Apu Kumar Saha

  3. School of Computer Science, University of Technology Sydney, Sydney, NSW, Australia

    Mukesh Prasad

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Vura, S., Devi, C.R.Y. (2023). A Novel Hybrid Compression Algorithm for Remote Sensing Imagery. In: Sharma, H., Saha, A.K., Prasad, M. (eds) Proceedings of International Conference on Intelligent Vision and Computing (ICIVC 2022). ICIVC 2022. Proceedings in Adaptation, Learning and Optimization, vol 17. Springer, Cham. https://doi.org/10.1007/978-3-031-31164-2_8

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