Unbalancing data with wavelet transformations
Brani Vidaković · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1995
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.