Joint reconstruction of interrupted SAR imagery for persistent surveillance change detection

Ivana Stojanovic; Les Novak; W. Clem Karl

doi:10.1117/12.2020653

23 May 2013 Joint reconstruction of interrupted SAR imagery for persistent surveillance change detection

Ivana Stojanovic, Les Novak, W. Clem Karl

Proceedings Volume 8746, Algorithms for Synthetic Aperture Radar Imagery XX; 87460L (2013) https://doi.org/10.1117/12.2020653
Event: SPIE Defense, Security, and Sensing, 2013, Baltimore, Maryland, United States

Abstract

In this paper we present a new method for restoring multi-pass synthetic aperture radar (SAR) images containing arbitrary gaps in SAR phase history data. Frequency and aspect gaps in SAR image spectrum manifest themselves as artifacts in the associated SAR imagery. Our approach, which we term LDREG for the (cursive ell);₁ difference regularization, jointly processes multi-pass interrupted data using sparse magnitude and sparse magnitude difference constraints, and results in improved quality imagery. We find that the joint processing of LDREG results in coherent change detection gains over independent processing of each data pass. To illustrate the capabilities of LDREG, we evaluate coherent change detection performance using images from the Gotcha SAR.

Citation Download Citation

Ivana Stojanovic, Les Novak, and W. Clem Karl "Joint reconstruction of interrupted SAR imagery for persistent surveillance change detection", Proc. SPIE 8746, Algorithms for Synthetic Aperture Radar Imagery XX, 87460L (23 May 2013); https://doi.org/10.1117/12.2020653

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