We present the implementation of a procedure to adapt an Asymmetric Wiener Filtering (AWF) methodology aimed to detect and discard ghost signal due to azimuth ambiguities in SAR images to the case for X-band Cosmo Sky Med (CSK) images in the framework of SEASAFE (Slick Emissions And Ship Automatic Features Extraction) project, developed at the Department of Science and Technology Innovation of the University of Piemonte Orientale, Alessandria, Italy. SAR is a useful tool to daily and nightly monitoring of the sea surface in all weather conditions. SEASAFE project is a software platform developed in IDL language able to process data in C- Land X-band SAR images with enhanced algorithm modules for land masking, sea pollution (oil spills) and ship detection; wind and wave evaluation are also available. In this contest, the need to individuate and discard false alarms is a critical requirement. The azimuth ambiguity is one of the main causes that generate false alarm in the ship detection procedure. Many methods to face with this problem were proposed and presented in recent literature. After a review of different approach to this problem, we describe the procedure to adapt the AWF approach presented in [1,2] to the case of X-band CSK images by implementing a selective blocks approach.
An automatic system called OSAD (Oil Spill Automatic Detector), able to discriminate oil spills (OS) from similar features (look-alikes – LA) in SAR images, was developed some years ago. Slick detection is based on a probabilistic method (tuned with a training dataset defined by an expert photointerpreter) evaluating radiometric and geometric characteristics of the areas of interest. OSAD also provides wind field by analyzing SAR images. With the aim to completely classify sea slicks, recently a new procedure has been added. Dark areas are identified on the image and the wind is computed inside and outside for every area: if outside wind value is less than a threshold of 2 m/s it is impossible to evaluate if damping is due to a slick. On the other hand, if outside wind is higher than the threshold and the difference between inside and outside the dark area is lower than 1 m/s we consider this reduction as wind fluctuation. Wind difference higher than 1 m/s is interpreted as damping effect due to a slick; therefore the remaining dark spots are split in OS and LA by OSAD. LA are then analyzed and separated in “biogenic” or “anthropogenic” slicks following an analogous procedure. The system performances has been tested on C-band SAR images, in particular on images having spatial resolution so high to examine details near the coastline; the obtained results confirm the efficiency of the algorithm in the classification of four types of signatures usually found on the sea surface.
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