Ship Detection From PolSAR Imagery Using the Complete Polarimetric Covariance Difference Matrix

In this paper, we proposed a complete polarimetric covariance difference matrix [
$CP$
]-based algorithm for ship detection in polarimetric synthetic aperture radar (PolSAR) imagery. To calculate [
$CP$
], we first developed a scheme to reflect the polarimetric scattering differences between ship pixel (SP) and its neighboring pixels (ISPs) and, then, dividedly accumulated the amplitude and phase differences between SP and ISPs. Compared to the polarimetric covariance difference matrix [
$P$
] developed in our earlier work, [
$CP$
] effectively overcomes the drawback of the lack of the phase information in [
$P$
]. To demonstrate the effectiveness of the proposed algorithm, we applied the [
$CP$
]-based ship detection algorithm to four PolSAR data sets, including one UAVSAR L-band data set with 21 ships, two AIRSAR L-band data sets with 11 and 22 ships, respectively, and one Radarsat-2 C-band data set with 8 ships. Experimental results show that: 1) the proposed algorithm can effectively detect ships with high target-to-clutter ratio (TCR) values and 2) [
$CP$
] has a better performance than the traditional polarimetric covariance matrix [
$C$
] and [
$P$
] on ship detection. To be more specific, the average TCR value of the proposed algorithm (23.86 dB) is 6.07 and 7.47 dB higher than PNF
$_{C}$
(i.e., the geometrical perturbation-polarimetric notch filter) and RS
$_{C}$
(i.e., the reflection symmetry method), respectively.