Spots segmentation in SAR images for remote sensing of environment

R. Araújo, F. Medeiros, Rodrigo C. S. Costa, R. Marques, R. B. Moreira, J.L. Silva
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引用次数: 1

Abstract

The paper proposes an algorithm to segment spots in synthetic aperture radar (SAR) images in order to support environmental remote monitoring. This approach consists of isolating dark areas that may have originated from oil pollution, thus achieving the aim of our investigation. The proposed algorithm combines a region growing approach and a multiscale analysis employed by an undecimated wavelet transform to localize dark areas in the sea. The undecimated wavelet applied to SAR images smooths the speckle noise while enhancing edges, thus providing a better result for the proposed segmentation algorithm that is achieved by a modified region growing approach. The minmax scheme is used to provide post processing of the segmented image. The algorithms were tested on real SAR images of oil spills.
环境遥感SAR图像的斑点分割
为了支持环境远程监测,提出了一种合成孔径雷达(SAR)图像中的斑点分割算法。这种方法包括隔离可能源于石油污染的黑暗区域,从而达到我们调查的目的。该算法结合了一种区域增长方法和一种基于未消差小波变换的多尺度分析方法来定位海洋中的暗区。将未消差小波应用于SAR图像,在平滑散斑噪声的同时增强边缘,从而为改进的区域增长方法实现的分割算法提供了更好的结果。采用最小最大值方案对分割后的图像进行后处理。该算法在真实的溢油SAR图像上进行了测试。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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