Name
Abstract | ||
|---|---|---|
In this paper we introduce wavelet video processing of proximity sensor signals. Proximity sensing is required for a wide range of military and commercial applications, including weapon fuzing, robotics, and automotive collision avoidance. While our proposed method temporarily increases signal dimension, it eventually performs data compression through the extraction of salient signal features. This data compression in tum reduces the necessary complexity of the remaining computational processing. We demonstrate our method of wavelet video processing via the proximity sensing of nearby objects through their Doppler shift. in doing this we perform a continuous wavelet transform on the Doppler signal, after subjecting if to a time-varying window. We then extract signal features from the resulting wavelet video, which we use as input to paftem recognition neural networks. The networks are trained to estimate the time-varying Doppler shift from the extracted features. We test the estimation performance of the networks, using different degrees of nonlinearity in the frequency shift over time and different levels of noise. We give the analytical result that the signal-to-noise enhancement of our proposed method is at least as good as the square root of the number of video frames, although more work is needed to completely quantify this. Real-time wavelet-based video processing and compression technology recently developed under the DOD WAVENET program offers an exciting opportunity to more fully investigate our proposed method. (C) 1998 SPIE and IS&T. [S1017-9909(98)01004-6]. |
Year | DOI | Venue |
|---|---|---|
1998 | 10.1117/1.482656 | JOURNAL OF ELECTRONIC IMAGING |
Keywords | Field | DocType |
video processing,signal processing,wavelet transforms,neural nets,signals,square roots,computations,data compression,video,doppler shift,detectors,continuous wavelet transform,doppler effect,pattern recognition,wavelets,compression,robotics,real time | Signal processing,Computer vision,Video processing,Proximity sensor,Pattern recognition,Computer science,Continuous wavelet transform,Video tracking,Artificial intelligence,Data compression,Wavelet transform,Wavelet | Journal |
Volume | Issue | ISSN |
7 | 4 | 1017-9909 |
Citations | PageRank | References |
0 | 0.34 | 1 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Steven E. Noel | 1 | 0 | 0.34 |
| Harold Szu | 2 | 149 | 38.33 |