Application of filtering efficiency prediction to hyperspectral data pre-processing - Lukin, Volodymyr; Krivenko, Sergiy; Rubel, Oleksii; Abramov, Sergey; Zriakhov, Mikhail; Uss, Mikhail; Vozel, Benoit; Chehdi, Kacem (Scientific Centre for Aerospace Research of the Earth Institute of Geological Science National Academy of Sciences of Ukraine, Kyiv, Ukraine, 2015)
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.