Wavelet-Based Hyperspectral Image Estimation

Ian Atkinson, Farzad Kamalabadi, Douglas L. Jones

Research output: Contribution to conferencePaperpeer-review


In this paper, we present a novel DFT- and wavelet-based estimation scheme for hyperspectral imagery. Optimal hyperspectral image estimation relies on the ability to decorrelate the signal in both space and channel at the cost of requiring second-order signal statistics. This statistical requirement is removed by the proposed estimator, which approximately decorrelates the signal in space using a 2-D discrete wavelet transform and in channel using a discrete Fourier transform. In addition to allowing extremely efficient estimation, the proposed estimator vastly improves visual quality and yields typical signal-to-noise ratio gains of over 14 dB.

Original languageEnglish (US)
Number of pages3
StatePublished - 2003
Event2003 IGARSS: Learning From Earth's Shapes and Colours - Toulouse, France
Duration: Jul 21 2003Jul 25 2003


Other2003 IGARSS: Learning From Earth's Shapes and Colours

ASJC Scopus subject areas

  • Computer Science Applications
  • General Earth and Planetary Sciences


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