Deconvolution of seismic data using adaptive Gaussian mixtures

نویسندگان

  • Ignacio Santamaría
  • Carlos Pantaleón
  • Jesús Ibáñez
  • Antonio Artés-Rodríguez
چکیده

Based on a Gaussian mixture model for the reflectivity sequence, we present a new technique for blind deconvolution of seismic data. The method obtains a deconvolution filter that maximizes at its output a measure of the relative entropy between the proposed Gaussian mixture and a pure Gaussian distribution. A new updating procedure for the mixture parameters is included in the algorithm: it allows us to apply the algorithm without any prior knowledge about the signal and noise. A simulation example illustrates the performance of the proposed method.

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عنوان ژورنال:
  • IEEE Trans. Geoscience and Remote Sensing

دوره 37  شماره 

صفحات  -

تاریخ انتشار 1999