Abstract
Motion estimation is a common ingredient in many state-of-the-art video processing algorithms, serving as an effective way to capture the spatial-temporal correlation in video signals. However, the robustness of motion estimation often suffers from problems such as ambiguities of motion trajectory (i.e. the aperture problem) and illumination variances. In this paper, we explore a new framework for video processing based on the recently proposed surfacelet transform. Instead of containing an explicit motion estimation step, the surfacelet transform provides a motion-selective subband decomposition for video signals. We demonstrate the potential of this new technique in a video denoising application.
Original language | English (US) |
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Title of host publication | Conference Record of the 40th Asilomar Conference on Signals, Systems and Computers, ACSSC '06 |
Pages | 883-887 |
Number of pages | 5 |
DOIs | |
State | Published - 2006 |
Event | 40th Asilomar Conference on Signals, Systems, and Computers, ACSSC '06 - Pacific Grove, CA, United States Duration: Oct 29 2006 → Nov 1 2006 |
Other
Other | 40th Asilomar Conference on Signals, Systems, and Computers, ACSSC '06 |
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Country/Territory | United States |
City | Pacific Grove, CA |
Period | 10/29/06 → 11/1/06 |
ASJC Scopus subject areas
- Signal Processing
- Computer Networks and Communications