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
Link To Document :
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