This paper presents a ship-detection study with Synthetic Aperture Radar (SAR) images acquired at two different frequencies: X-and C-band. The detection procedure relies on a novel algorithm based on the likelihood functions of both canonical ship target and sea clutter. Spaceborne images were acquired over the same area in the Solent Channel in UK at approximately the same time on the 7 th June 2016. Here, datasets are compared in terms of probability of detection (PD), probability of false alarm (PFA) and Target-to-Clutter Ratio (TCR). Detection maps are validated with Automatic Identification System (AIS) data when available and preliminary results show a higher TCR for the X-band SAR image.
Satellite image mosaics are commonly used for large-scale mapping purposes. Perpetual cloud cover may prohibit the mapping with electro-optical satellite imagery within a reasonable time interval, e.g. in tropical areas. In these cases, the additional use of SAR data can help to complement the image of the earth surface, as cloudindependent spaceborne SAR data has been proven to be a valuable thematic and topographic mapping source [1]. An effective way to realize an integrated image mosaic is the colorization of high-resolution SAR imagery by applying statistical filters and the adaptation of these false colors with respect to an optical reference. The creation of SAR images with a land-cover related color scheme has been shown before [2]. But generally, the resulting images have no relationship to the color impression of an optical scene. The motivation of the technique described in this paper is to create automatically colour classified products directly from single polarized SAR images to create seamless mosaics from colored SAR images to mosaic colored SAR images with electro-optical imagery
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