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Simultaneous least squares wavelet decomposition for multidimensional irregularly spaced data

Shahbazian, M ; Sharif University of Technology | 2013

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  1. Type of Document: Article
  2. DOI: 10.4028/www.scientific.net/AMM.239-240.1213
  3. Publisher: 2013
  4. Abstract:
  5. The multidimensional Discrete Wavelet Transform (DWT) has been widely used in signal and image processing for regularly sampled data. For irregularly sampled data, however, other techniques should be used including the Least Square Wavelet Decomposition (LSWD). The commonly used level by level (sequential) wavelet decomposition, which calculates the wavelet coefficients in each resolution separately, may result in a gross interpolation error. To overcome this drawback, a different approach called the Simultaneous Least Square Wavelet Decomposition, which computes all wavelet coefficients simultaneously, have been proposed by the authors. In this paper, we extend the simultaneous LSWD approach to the multidimensional case and show that this method has excellent reconstruction property for two dimensional irregularly spaced data
  6. Keywords:
  7. Irregular data ; Least squares ; Multidimensional ; Signal reconstruction ; Wavelet ; Interpolation error ; Irregular data ; Least Square ; Multi-dimensional case ; Multidimensional ; Reconstruction property ; Sampled data ; Signal and image processing ; Wavelet ; Wavelet coefficients ; Discrete wavelet transforms ; Image processing ; Signal reconstruction ; Wavelet decomposition
  8. Source: Applied Mechanics and Materials, Guangzhou ; Volume 239-240 , 2013 , Pages 1213-1218 ; 16609336 (ISSN) ; 9783037855454 (ISBN)
  9. URL: http://www.scientific.net/AMM.239-240.1213