Prediction Of DCT-Based Denoising Efficiency For Images Corrupted By Signal-Dependent Noise

S. Krivenko (1) , V. Lukin (1) , Benoit Vozel (2) , Kacem Chehdi (2)

1 Kharkov National University
2 IETR - Institut d'Électronique et des Technologies du numéRique

Mots clés: discrete cosine transforms; image denoising; DCT-based filtering; MSE; PSNR-HVS-M; discrete cosine transform; hyperspectral sensing; image denoising efficiency; radar remote sensing; signal-dependent noise; traditional quality criteria; visual quality metrics; Accuracy; Filtering; Fitting; Noise; Noise reduction; Remote sensing; DCT; efficiency prediction

Domaines: Traitement du signal et de l'image [eess.SP]

S. Krivenko, V. Lukin, Benoit Vozel, Kacem Chehdi. Prediction Of DCT-Based Denoising Efficiency For Images Corrupted By Signal-Dependent Noise. IEEE 34th International Conference on Electronics and Nanotechnology (ELNANO), Apr 2014, Kiev, Ukraine. http://www.ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6873920&isnumber=6873425, ⟨10.1109/ELNANO.2014.6873920⟩. ⟨hal-01111036⟩