Directional Tight Framelet Filter Bank Design

  • Author / Creator
    Che, Menglu
  • It is well known that most information of an image is contained in its edges. Therefore
    capturing edges in an image is of fundamental importance in image processing. Tensor
    product real-valued wavelets only capture edges along the horizontal and vertical direc-
    tions. Hence they are only suboptimal for handling high-dimensional problems. In this
    thesis we use a framelet-based approach to enhance the performance of tensor product
    real-valued wavelets. By employing an additional high-pass filter, we construct finitely
    supported complex-valued tight framelet filter banks {a;b1,b2} such that their tensor
    products in dimension two offer four directions along 0◦(horizontal), 45◦, 90◦(vertical)
    and 135◦. We propose a simple and effective algorithm to construct such directional
    tight framelet filter banks, and provide a necessary and sufficient condition for their
    existence. Finally, several concrete examples of such directional tight framelet filter
    banks are given.

  • Subjects / Keywords
  • Graduation date
    Fall 2013
  • Type of Item
  • Degree
    Master of Science
  • DOI
  • License
    This thesis is made available by the University of Alberta Libraries with permission of the copyright owner solely for non-commercial purposes. This thesis, or any portion thereof, may not otherwise be copied or reproduced without the written consent of the copyright owner, except to the extent permitted by Canadian copyright law.