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F G Carrozzo1, A Raponi1, M C De Sanctis1

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This study introduces a new method to reduce noise in Visible and InfraRed (VIR) hyperspectral images from NASA's Dawn mission. The technique significantly improves data quality for analyzing celestial bodies like Vesta and Ceres.

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Area of Science:

  • Planetary Science
  • Remote Sensing
  • Spectroscopy

Background:

  • Remote sensing images, including hyperspectral data, are prone to noise like stripes and spikes.
  • These artifacts in Visible and InfraRed (VIR) spectrometer data from NASA's Dawn mission can distort spectral information and lead to misinterpretations of surface composition.

Purpose of the Study:

  • To develop and present a robust technique for minimizing artifacts in VIR hyperspectral data.
  • To enhance the quality of spectral data for accurate analysis of celestial surfaces, specifically Vesta and Ceres.

Main Methods:

  • A two-step artifact correction process was developed, involving artifact matrix creation and application.
  • The method incorporates a new instrument response function using ground and in-flight radiometric measurements.
  • Specific corrections address spectral spikes, odd-even band effects, vertical stripes, and high-frequency noise using polynomial fitting.

Main Results:

  • The applied corrections significantly improved the quality of the VIR hyperspectral data.
  • The enhanced data quality facilitates more reliable spectral analysis of planetary surfaces.
  • Comparison with ground telescopic spectra of Vesta and Ceres demonstrated the effectiveness of the artifact removal.

Conclusions:

  • The presented technique effectively minimizes systematic artifacts in VIR hyperspectral data.
  • Improved data quality enhances the significance and accuracy of spectral analyses for planetary bodies.
  • This method provides a valuable tool for processing and interpreting hyperspectral imagery from space missions.