A Novel Noise Removal Method Using Neural Networks

Autor: Catalina Lucia COCIANU, Alexandru Daniel STAN
Jazyk: English<br />Romanian; Moldavian; Moldovan
Rok vydání: 2016
Předmět:
Zdroj: Informatică economică, Vol 20, Iss 3, Pp 66-75 (2016)
Druh dokumentu: article
ISSN: 1453-1305
1842-8088
14531305
DOI: 10.12948/issn14531305/20.3.2016.07
Popis: In this paper is presented a new technique consisting in applying some pre-whitening and shrinkage methods followed by a neural network-based supervised approach for correlated noise removal purposed. In our work the type of noise and the covariance matrix of noise are known or can be estimated using the “white wall” method. Due to data dimensionality, a PCA-based compression technique is used to obtain a tractable solution. The local memories of the neurons are determined using a supervised learning process based on the compressed pre-processed inputs and the compressed version of the original images. The proposed method is evaluated using some of the most commonly used indicators and the results are reported in the third section of the paper. The conclusive remarks together with suggestions for further work are supplied in the final part of the paper.
Databáze: Directory of Open Access Journals