Pretrained network models and demo codes for EUVIP's 2021

Please refer to the following paper:

M.Ponomarenko, O. Miroshnichenko, V. Lukin and K. Egiazarian, "Blind estimation and supression of additive spatially correlated Gaussian noise in images", EUVIP, 2021, 6p.

euvip2021_demos.zip - Pretrained network models and demo codes (348 Mb).

nlnet.mat - pretrained NLNet

spnet.mat - pretrained SPNet

drunet.mat - pretrained DRUNet, convertd to Matlab

bm3d_spnet_m1.m - demo script for BM3D+SPNet+M1 denoising scheme

drunet_nlnet_m2.m - demo script for DRUNet+NLNet+M2 denoising scheme

tst.png - fragment of real life image with a spatially correlated noise

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Last changed: 2021-06-23.

Please refer to the following paper: M.Ponomarenko, O. Miroshnichenko, V. Lukin and K. Egiazarian, "Blind estimation and supression of additive spatially correlated Gaussian noise in images", EUVIP, 2021, 6p.

Please refer to the following paper:

M.Ponomarenko, O. Miroshnichenko, V. Lukin and K. Egiazarian, "Blind estimation and supression of additive spatially correlated Gaussian noise in images", EUVIP, 2021, 6p.