@inproceedings{37b528e25a8a40afa039ea741d1cfd10,
title = "Mixed norm-based image restoration using neural network",
abstract = "In this paper, a novel image restoration model is presented based on the adaptive mixed norm regularization and Hop field neural network. The new error function of this image restoration model combines the L2-norm and L1-norm. To fit the neural network processing, the nonlinear gradient operator of L1-norm is decomposed to the sum of linear operators. Two methods of calculating the adaptive scale control parameter and the modified implementation technique using neural network are presented. Experimental results demonstrate the proposed algorithms are more effective than the traditional and total variation image restoration algorithms.",
keywords = "Image restoration, Mixed norm, Neural network, Regularization",
author = "Xu, \{Yuan Nan\} and Jing Wang and Dong, \{Yan Bing\} and Jin Chenfei and Zhao Yuan",
year = "2013",
doi = "10.1109/GreenCom-iThings-CPSCom.2013.365",
language = "英语",
isbn = "9780769550466",
series = "Proceedings - 2013 IEEE International Conference on Green Computing and Communications and IEEE Internet of Things and IEEE Cyber, Physical and Social Computing, GreenCom-iThings-CPSCom 2013",
pages = "1957--1961",
booktitle = "Proceedings - 2013 IEEE International Conference on Green Computing and Communications and IEEE Internet of Things and IEEE Cyber, Physical and Social Computing, GreenCom-iThings-CPSCom 2013",
note = "2013 IEEE International Conference on Green Computing and Communications and IEEE Internet of Things and IEEE Cyber, Physical and Social Computing, GreenCom-iThings-CPSCom 2013 ; Conference date: 20-08-2013 Through 23-08-2013",
}