1 September 1995 Unbalancing data with wavelet transformations
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Abstract
Discrete wavelet transformations have become indispensable analytical tools in data compression and data denoising. In this paper we give some empirical accounts of wavelet transformations and propose novel thresholding and wavelet selection methods. This is achieved via connections with measures of inequality, that have been used in economics for a long time. We compare our methods with standard thresholding and wavelet selection procedures.
© (1995) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Brani Vidakovic "Unbalancing data with wavelet transformations", Proc. SPIE 2569, Wavelet Applications in Signal and Image Processing III, (1 September 1995); doi: 10.1117/12.217638; https://doi.org/10.1117/12.217638
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