PolSAR Ship Detection Based on Neighborhood Polarimetric Covariance Matrix^1


Liu T, Yang Z, Marino A, Gao G & Yang J (2020) PolSAR Ship Detection Based on Neighborhood Polarimetric Covariance Matrix^1. IEEE Transactions on Geoscience and Remote Sensing.

The detection of small ships in polarimetric synthetic aperture radar (PolSAR) images is still a topic for further investigation. Recently, patch detection techniques, such as superpixel-level detection, have stimulated wide interest because they can use the information contained in similarities among neighboring pixels. In this article, we propose a novel neighborhood polarimetric covariance matrix (NPCM) to detect the small ships in PolSAR images, leading to a significant improvement in the separability between ship targets and sea clutter. The NPCM utilizes the spatial correlation between neighborhood pixels and maps the representation for a given pixel into a high-dimensional covariance matrix by embedding spatial and polarization information. Using the NPCM formalism, we apply a standard whitening filter, similar to the polarimetric whitening filter (PWF). We show how the inclusion of neighborhood information improves the performance compared with the traditional polarimetric covariance matrix. However, this is at the expense of a higher computation cost. The theory is validated via the simulated and measured data under different sea states and using different radar platforms.

Marine vehicles; Covariance matrices; Detectors; Correlation; Synthetic aperture radar; Clutter; Scattering

Output Status: Forthcoming/Available Online

IEEE Transactions on Geoscience and Remote Sensing

StatusIn Press
Publication date online30/09/2020
Date accepted by journal04/09/2020
PublisherInstitute of Electrical and Electronics Engineers (IEEE)