• 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