@inproceedings{uss:hal-03003494,
TITLE = {Comparison of learning-based and maximum-likelihood estimators of image noise variance for real-life and synthetic anisotropic textures},
AUTHOR = {Uss, M. and Vozel, B. and Lukin, V. and Chehdi, K.},
URL = {https://hal.science/hal-03003494},
BOOK
TITLE = {Image and Signal Processing for Remote Sensing XXVI 2020},
ADDRESS = {Edinburgh, United Kingdom},
EDITOR = {Bruzzone L.Bovolo F.Santi E.},
PUBLISHER = {SPIE},
SERIES = {Proceedings of SPIE - The International Society for Optical Engineering},
VOLUME = {11533},
PAGES = {1153303},
YEAR = {2020},
MONTH = Sep, DOI = {10.1117/12.2573934},
KEYWORDS = {Anisotropic fractional Brownian motion ; Blind noise parameter estimation ; Convolutional neural network ; Deep regression with uncertainty ; Experimental data ; Hard mining ; Multivariate noise variance model ; Signal-dependency},
HAL_ID = {hal-03003494},
HAL_VERSION = {v1},
}