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Proceedings Paper

Noise filtering of interferometric SAR images
Author(s): Jong-Sen Lee; Thomas L. Ainsworth; Mitchell R. Grunes; Raymond M. Goldstein
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Paper Abstract

The interferometric SAR with two antennas aligned in the along-track direction is capable of mapping the ocean current field, and in the cross-track direction can be used for topographic mapping. Like amplitude SAR images, interferometric phase images are susceptible to speckle and other noise sources due to decorrelations by thermal noise, spatial baseline, etc. (Zebker, et al.,1992). The noise effect is more pronounced in the space-borne multi-pass interferometry for topographic mapping due to long baseline and temporal decorrelations. However, unlike the SAR images, in which noise is characterized by a multiplicative noise model, the noise in the phase image has properties of additive noise, and the noise standard deviation depends on the corre-lation coefficient between two SAR complex images. In this paper, two additive noise filtering algorithms,i.e. the sigma filter and the local statistics filter, are adapted to the statistical characteristics of the phase image (after the phase unwrapping). The basic idea is to apply more filtering action in areas with a lower correlation coefficient (high noise level), and less filtering in areas with a higher correlation coefficient. An ideal noise filter for the phase image should be able to smooth the noise, while retaining the spatial resolution and radiometric information.

Paper Details

Date Published: 30 December 1994
PDF: 8 pages
Proc. SPIE 2315, Image and Signal Processing for Remote Sensing, (30 December 1994); doi: 10.1117/12.196772
Show Author Affiliations
Jong-Sen Lee, Naval Research Lab. (United States)
Thomas L. Ainsworth, Naval Research Lab. and Allied-Signal Technical Service Corp. (United States)
Mitchell R. Grunes, Naval Research Lab. and Allied-Signal Technical Service Corp. (United States)
Raymond M. Goldstein, Jet Propulsion Lab. (United States)

Published in SPIE Proceedings Vol. 2315:
Image and Signal Processing for Remote Sensing
Jacky Desachy, Editor(s)

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