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Link to original content: https://doi.org/10.1007/s11042-020-08829-2
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Edge preserved multispectral image compression using PCA and hybrid transform

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Abstract

In multispectral image compression, it is difficult to obtain sparse approximation for images with rich details. The existing methods produce better results under some constraints on image content. In order to obtain robust multispectral image compression, the Principal Component Analysis (PCA) method is used to reduce the spectral redundancy and the sparse approximation is obtained by using Extended Shearlet Transform (EST) and Tetrolet Transform(TT). The anisotropic property of EST is used to preserve smooth images with global structures of an image whereas the TT is used to preserve the local structures. The performance of proposed method is compared with the existing methods in terms of rate distortion and information preservation perspectives. The Compression Ratio (CR) and Peak Signal to Noise Ratio (PSNR) are used as rate-distortion measure. The Mean Structural Similarity Index Metric (MSSIM) and Kappa coefficient (K) are information preservation measures. The simulation results show that the proposed EPMI-HT method outperforms the existing hybrid methods for all kinds of image content at high CR with retaining edge information.

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Authors and Affiliations

  1. Department of ECE, Kalasalingam Institute of Technology, Krishnankoil, Tamilnadu, 626126, India

    S. Thayammal

  2. Department of CSE, P.S.R. Engineering College, Sivakasi, Tamilnadu, 626140, India

    S. Priyadarsini

  3. Department of ECE, Mepco Schlenk Engineering College, Sivakasi, Tamilnadu, 626 005, India

    D. Selvathi

Authors
  1. S. Thayammal
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  2. S. Priyadarsini
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  3. D. Selvathi
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Correspondence to S. Thayammal.

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Thayammal, S., Priyadarsini, S. & Selvathi, D. Edge preserved multispectral image compression using PCA and hybrid transform. Multimed Tools Appl 79, 20133–20148 (2020). https://doi.org/10.1007/s11042-020-08829-2

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  • DOI: https://doi.org/10.1007/s11042-020-08829-2

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