DocumentCode
1968709
Title
Texture estimation with neural networks
Author
Bourgeois, Brian ; Walker, Charles
Author_Institution
Naval Oceanogr. & Atmos. Res. Lab., Stennis Space Center, MS, USA
fYear
1991
fDate
15-17 Aug 1991
Firstpage
99
Lastpage
106
Abstract
The authors investigate the use of neural networks for the direct estimation of image texture. Unlike previous approaches where networks are used to make decisions on feature vectors derived from traditional techniques, or where a network is trained to perform the function of a traditional technique, the proposed approach uses a network to directly model texture. The envisioned approaches to this method are described. Preliminary results of one-dimensional tests show that a neural network implementation is very adapt at recognizing irregular signals, even in the presence of added noise. This is intended to be applied in a Seafloor Acoustic Imagery via sidescan imagery
Keywords
neural nets; signal processing; sonar; added noise; image texture; irregular signals; neural networks; one-dimensional tests; texture estimation; Computer networks; Image processing; Image texture; Image texture analysis; Laboratories; Layout; Neural networks; Nonlinear systems; Simulated annealing; Sonar;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks for Ocean Engineering, 1991., IEEE Conference on
Conference_Location
Washington, DC
Print_ISBN
0-7803-0205-2
Type
conf
DOI
10.1109/ICNN.1991.163332
Filename
163332
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