Abstract
Synthetic aperture radar (SAR) images are widely used for aerial and spatial image applications, such as terrain classification, target detection, etc. SAR images in different bands can provide multi-spectrum information, which is beneficial for more accurate target observation. In this paper, a new method is proposed for joint detection of roads in multiband SAR images. First, the multi-segmented polyline model is introduced to provide a more accurate description of road curve. Then, the roads in SAR images are extracted in a Bayesian tracking framework, and the particle filtering algorithm is employed to implement the tracking. Finally, a joint detection method is proposed to determine the optimal weights of particles based on the maximum likelihood (ML) criterion. The effectiveness of the proposed method is demonstrated by experimental results with real multiband SAR data.
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