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Multi-window Gabor schemes in signal and image representations

  • Yehoshua Y. Zeevi
  • Meir Zibulski
  • Moshe Porat
Part of the Applied and Numerical Harmonic Analysis book series (ANHA)

Abstract

Motivated by biological vision, schemes of signal and image representation by localized Gabor-type functions are introduced and analyzed. These schemes, suitable for information representation in a combined frequency-position space are investigated through signal decomposition into a set of elementary functions. Utilizing the Piecewise Zak transform (PZT), the theory of the multi-window approach is given in detail based on the mathematical concept of frames. The advantages of using more than a single window are analyzed and discussed. Applications to image processing and computer vision are presented with regard to texture images, and considered in the context of two typical tasks: image representation by partial information and pattern recognition. In both cases the results indicate that the multi-window approach is efficient and superior in major aspects to previously available methods. It is concluded that the new multi-window Gabor approach could be integrated efficiently into practical techniques of signal and image representation.

Keywords

Spatial Frequency Window Function Image Representation Tight Frame Dual Frame 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media New York 1998

Authors and Affiliations

  • Yehoshua Y. Zeevi
  • Meir Zibulski
  • Moshe Porat

There are no affiliations available

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