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Research Article | Open Access |

Method for Determination of Support Length of Daubechies Basis Function for Wavelet MRA based Moving Characteristic Estimation

Author 1: Kohei Arai
International Journal of Advanced Computer Science and Applications (IJACSA) · Vol. 12, No. 6 · Published 2021

DOI: https://doi.org/10.14569/IJACSA.2021.0120621

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Abstract

Method for determination of support length of Daubechies basis function for wavelet Multi Resolution Analysis: MRA based moving characteristic estimation is proposed. The method based on root mean square difference between original and reconstructed image from just a low frequency component from MRA. Also, one of applications of the method for detection and tracking of moving targets, typhoon and boundary between warm and cold current observed from satellite remote sensing images is shown. It is found that the proposed method allows to detect and to track for moving targets of a typhoon and a boundary in the time series of GOES images.

Keywords

Multi-dimensional wavelet transformation multi resolution analysis: MRA moving target detection support length typhoon movement boundary detection and tracking

How to Cite this Article

Arai, K. (2021). Method for Determination of Support Length of Daubechies Basis Function for Wavelet MRA based Moving Characteristic Estimation. International Journal of Advanced Computer Science and Applications, 12(6). https://doi.org/10.14569/IJACSA.2021.0120621

Arai, Kohei. "Method for Determination of Support Length of Daubechies Basis Function for Wavelet MRA based Moving Characteristic Estimation." International Journal of Advanced Computer Science and Applications, vol. 12, no. 6, 2021, https://doi.org/10.14569/IJACSA.2021.0120621.

@article{Arai2021,
  title     = {Method for Determination of Support Length of Daubechies Basis Function for Wavelet MRA based Moving Characteristic Estimation},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {12},
  number    = {6},
  year      = {2021},
  publisher = {The Science and Information Organization},
  author    = {Kohei Arai},
  doi       = {10.14569/IJACSA.2021.0120621},
  url       = {https://doi.org/10.14569/IJACSA.2021.0120621}
}

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