APPLICATION OF FILTERING EFFICIENCY PREDICTION TO HYPERSPECTRAL DATA PRE-PROCESSING

  • V. V. Lukin National Aerospace University, Kharkov, Ukraine
  • S. S. Krivenko National Aerospace University, Kharkov, Ukraine
  • O. S. Krivenko National Aerospace University, Kharkov, Ukraine
  • S. K. Abramov National Aerospace University, Kharkov, Ukraine
  • M. S. Zriakhov National Aerospace University, Kharkov, Ukraine
  • M. L. Uss National Aerospace University, Kharkov, Ukraine
  • B. Vozel University of Rennes 1, Lannion, France
  • K. Chehdi University of Rennes 1, Lannion, France

Abstract

Several approaches to prediction image denoising efficiency for DCT-based filter have been proposed recently. They allow predicting improvement of PSNR (IPSNR) and visual quality metrics as PSNR-HVS-M (IPHVS) for denoised images under condition of noise characteristics known or pre-estimated in advance. Here we apply the prediction approach to pre-processing ten sub-bands of Hyperion hyperspectral data. It is shown that there are sub-band images for which there is no necessity to carry out filtering. Meanwhile, there are sub-bands for which IPSNR reaches 5…9 dB and the use of denoising is expedient.
Section
Techniques for Earth observation data acquisition, processing and interpretation