Neural Architectures for Correlated Noise Removal in Image Processing
Joint Authors
Cocianu, Catalina
Stan, Alexandru
Source
Mathematical Problems in Engineering
Issue
Vol. 2016, Issue 2016 (31 Dec. 2016), pp.1-14, 14 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2016-04-19
Country of Publication
Egypt
No. of Pages
14
Main Subjects
Abstract EN
The paper proposes a new method that combines the decorrelation and shrinkage techniques to neural network-based approaches for noise removal purposes.
The images are represented as sequences of equal sized blocks, each block being distorted by a stationary statistical correlated noise.
Some significant amount of the induced noise in the blocks is removed in a preprocessing step, using a decorrelation method combined with a standard shrinkage-based technique.
The preprocessing step provides for each initial image a sequence of blocks that are further compressed at a certain rate, each component of the resulting sequence being supplied as inputs to a feed-forward neural architecture FX→FH→FY.
The local memories of the neurons of the layers FH and FY are generated through a supervised learning process based on the compressed versions of blocks of the same index value supplied as inputs and the compressed versions of them resulting as the mean of their preprocessed versions.
Finally, using the standard decompression technique, the sequence of the decompressed blocks is the cleaned representation of the initial image.
The performance of the proposed method is evaluated by a long series of tests, the results being very encouraging as compared to similar developments for noise removal purposes.
American Psychological Association (APA)
Cocianu, Catalina& Stan, Alexandru. 2016. Neural Architectures for Correlated Noise Removal in Image Processing. Mathematical Problems in Engineering،Vol. 2016, no. 2016, pp.1-14.
https://search.emarefa.net/detail/BIM-1112417
Modern Language Association (MLA)
Cocianu, Catalina& Stan, Alexandru. Neural Architectures for Correlated Noise Removal in Image Processing. Mathematical Problems in Engineering No. 2016 (2016), pp.1-14.
https://search.emarefa.net/detail/BIM-1112417
American Medical Association (AMA)
Cocianu, Catalina& Stan, Alexandru. Neural Architectures for Correlated Noise Removal in Image Processing. Mathematical Problems in Engineering. 2016. Vol. 2016, no. 2016, pp.1-14.
https://search.emarefa.net/detail/BIM-1112417
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1112417