Detecting Arctic Icebergs in Sea Ice in L-Band SAR Images Using a Multiscale CFAR Algorithm

This study proposes a multiscale extension of the well-known constant false alarm rate (CFAR) outlier detection method for the detection of icebergs in L-band synthetic aperture radar (SAR) images. The proposed method offers the possibility to accurately detect both single icebergs or clusters of icebergs embedded in sea ice. The method was tested on 8 L-band dual-pol SAR images acquired at various incidence angles and compared against a conventional single-scale CFAR approach. Ground-truth iceberg locations were derived from optical satellite images to ensure accurate validation of the results. The results reveal that the multiscale method improves the detection performance for icebergs of all sizes with an increase in recall of 0.05 and precision of 0.04 on average, leading to an increase in F1 score of 0.05 on average. In addition, the suggested multiscale method improves the estimation of the total iceberg area compared to a single-scale method, with a relative error of the estimated total area of 0.53 on average, compared to 1.05 for the multiscale approach. The results demonstrate the feasibility of using a multiscale outlier detection method on SAR images for the operational detection of icebergs in sea ice.