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Proceedings Paper

Filtering of weather radar imagery using steerable Gaussian smoothers
Author(s): Dimitrios Charalampidis; Anirudh Paduru
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Paper Abstract

Large-scale weather radar signatures are easier to identify compared to smaller-scale events. The location of such signatures can be predicted and tracked. Thus, large-scale signatures are useful in forecasting. Identification of these signatures in radar imagery can be facilitated through the use of smoothing filters. In particular, processing of radar imagery using directional smoothers has been shown to be more effective in retaining the storm front characteristics compared to isotropic smoothers. Moreover, efficient directional smoothing techniques have been developed that are capable of quickly processing large amounts of data. An advantage of smoothers operating in the spatial domain is that they are capable of involving logical operations in order to determine which pixels should be processed or neglected. This paper extents a recently introduced computationally efficient separable/steerable Gaussian-based smoothing technique in three aspects. First, the technique is generalized so that computationally efficient filters having shapes other than Gaussian with respect to their main orientation can be designed. Second, it is shown that the technique presented in this work is more efficient that the commonly used angular harmonic expansion. Third, a technique that combines directional and isotropic filtering is introduced. The technique is capable of revealing directional structures hidden in large-scale signatures, and thus be employed as a preprocessing step in forecasting applications.

Paper Details

Date Published: 29 April 2009
PDF: 11 pages
Proc. SPIE 7308, Radar Sensor Technology XIII, 730811 (29 April 2009); doi: 10.1117/12.819088
Show Author Affiliations
Dimitrios Charalampidis, Univ. of New Orleans (United States)
Anirudh Paduru, Univ. of New Orleans (United States)

Published in SPIE Proceedings Vol. 7308:
Radar Sensor Technology XIII
Kenneth I. Ranney; Armin W. Doerry, Editor(s)

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