The design of spatio-temporal filters to estimate velocity has been dominated by the frequency domain approach. Filters are designed to be as compact as possible in frequency domain for velocity resolution and compact in the spatial domain for good spatial resolution. An alternative is to design filters such that their outputs are maximally informative. An information theoretic analysis highlights the importance of the input prior in filter design. Under the assumption of a simple input or that only the dominant component of a complex input needs to be estimated, it is shown that a filter bank of broadly tuned filters can be used to accurately estimate the input frequency. For such inputs there is an incremental gain in information at a huge increase in cost for filter banks using sets of filters tuned narrower than a certain width. The issues of resolution and complex inputs are also addressed. The output of a filter bank encodes information in a redundant manner making it robust to noise in the system. By developing a probability measure it is possible to make the output of the system generate probability distributions of parameter. Examples for orientation, spatial and temporal frequency are given.

Date Published: 11 October 1994
PDF: 12 pages
Proc. SPIE 2303, Wavelet Applications in Signal and Image Processing II, (11 October 1994); doi: 10.1117/12.188802

Published in SPIE Proceedings Vol. 2303:
Wavelet Applications in Signal and Image Processing II
Andrew F. Laine; Michael A. Unser, Editor(s)