2D wavelet-based spectra with applications

Orietta Nicolis, Pepa Ramírez-Cobo, Brani Vidakovic

Resultado de la investigación: Contribución a una revistaArtículorevisión exhaustiva

23 Citas (Scopus)

Resumen

A wavelet-based spectral method for estimating the (directional) Hurst parameter in isotropic and anisotropic non-stationary fractional Gaussian fields is proposed. The method can be applied to self-similar images and, in general, to d-dimensional data which scale. In the application part, the problems of denoising 2D fractional Brownian fields and classification of digital mammograms to benign and malignant are considered. In the first application, a Bayesian inference calibrated by information from the wavelet-spectral domain is used to separate the signal from the noise. In the second application, digital mammograms are classified into benign and malignant based on the directional Hurst exponents which prove to be discriminatory summaries.

Idioma originalInglés
Páginas (desde-hasta)738-751
Número de páginas14
PublicaciónComputational Statistics and Data Analysis
Volumen55
N.º1
DOI
EstadoPublicada - 1 ene 2011

Áreas temáticas de ASJC Scopus

  • Estadística y probabilidad
  • Matemática computacional
  • Teoría computacional y matemáticas
  • Matemáticas aplicadas

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