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Proceedings Paper

Performance analysis of SAR change detection technique
Author(s): Pierfrancesco Lombardo; G. Fedele; Debora Pastina
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Paper Abstract

The recent advance and diffusion of airborne and satellite SAR systems makes the use of multitemporal SAR images of practical interest for monitoring and control applications, especially when aiming at the identification of moving objects. Change detection is a powerful technique, which allows the detection of slowly moving targets. This is obtained by subtracting on a pixel-by-pixel basis the intensity of two SAR images collected at different times and comparing the absolute value of the difference to a detection threshold. Under ideal conditions, the fixed background is totally correlated and cancels out completely. On the contrary, a slowly moving target changes its position in the two images and is not cancelled. Therefore only its echo crosses the threshold. In practice, a number of factors cause the deviation from the ideal conditions; among the others the temporal decorrelation of the scene due to the internal clutter motion and the presence of misregistration and miscalibration errors. The prediction of change detection performance is essential to the design of SAR based systems for the moving target detection and should take into account all of the possible mismatch causes. In the present paper we aim at a complete mathematical characterization of the performance of change detection under non-ideal conditions. Specifically, Section 2 introduces the change detection technique and discusses some of the possible deviations from the ideal conditions. The analytical derivations are presented in Section 3, together with the discussion of the achieved results. To validate the theory, the obtained performance prediction is compared to the results obtained with real SAR images in Section 4.

Paper Details

Date Published: 4 December 1998
PDF: 12 pages
Proc. SPIE 3500, Image and Signal Processing for Remote Sensing IV, (4 December 1998); doi: 10.1117/12.331884
Show Author Affiliations
Pierfrancesco Lombardo, Univ. of Rome La Sapienza (Italy)
G. Fedele, Univ. of Rome La Sapienza (Italy)
Debora Pastina, Univ. of Rome La Sapienza (United Kingdom)


Published in SPIE Proceedings Vol. 3500:
Image and Signal Processing for Remote Sensing IV
Sebastiano Bruno Serpico, Editor(s)

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