Abstract
We propose a new scheme, named contourlet, that provides a flexible multiresolution, local and directional image expansion. The contourlet transform is realized efficiently via a double iterated filter bank structure. Furthermore, it can be designed to satisfy the anisotropy scaling relation for curves, and thus offers a fast and structured curvelet-like decomposition. As a result, the contourlet transform provides a sparse representation for two-dimensional piecewise smooth signals resembling images. Finally, we show some numerical experiments demonstrating the potential of contourlets in several image processing tasks.
Original language | English (US) |
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Pages (from-to) | 497-501 |
Number of pages | 5 |
Journal | Conference Record of the Asilomar Conference on Signals, Systems and Computers |
Volume | 1 |
State | Published - 2002 |
Event | The Thirty-Sixth Asilomar Conference on Signals Systems and Computers - Pacific Groove, CA, United States Duration: Nov 3 2002 → Nov 6 2002 |
ASJC Scopus subject areas
- Signal Processing
- Computer Networks and Communications