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Application of asymmetric mapping and selective filtering (AMSF) method to Cosmo/SkyMed images by implementation of a selective blocks approach for ship detection optimization in SEASAFE framework

机译:通过在SEASAFE框架中实施选择性块方法进行舰船检测优化,将非对称映射和选择性过滤(AM&SF)方法应用于Cosmo / SkyMed图像

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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- L-and 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 to the case of X-band CSK images by implementing a selective blocks approach.
机译:我们介绍了一种程序的实现,该程序适用于SEASAFE框架中针对X波段Cosmo Sky Med(CSK)图像的情况,旨在检测和丢弃由于SAR图像中方位角模糊而导致的幻像信号的非对称维纳滤波(AWF)方法(光滑排放和船舶自动特征提取)项目,由意大利亚历山德里亚·皮耶蒙特·东方大学的科技创新系开发。 SAR是在所有天气情况下每天和每晚监视海面的有用工具。 SEASAFE项目是一种以IDL语言开发的软件平台,能够处理具有C-L波段和X波段SAR图像的数据,并具有用于陆地掩蔽,海洋污染(溢油)和船舶检测的增强算法模块;还可以进行风浪评估。在这场比赛中,个性化和丢弃虚假警报的需求是至关重要的。方位歧义是在船舶检测程序中产生误报的主要原因之一。在最近的文献中提出并提出了许多解决这个问题的方法。在回顾了针对该问题的不同方法之后,我们描述了通过实现选择性块方法来使提出的AWF方法适应X波段CSK图像情况的过程。

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