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A SIMPLE AND EFFICIENT APPROACH FOR COARSE SEGMENTATION OF MOROCCAN COASTAL UPWELLING

机译:一种简单有效的摩洛哥沿海升值粗细分的方法

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In this work, we aim to develop a simple and fast algorithm using conventional methods in images segmentation for the automatic detection and extraction of upwelling areas, in the coastal region of Morocco, from the sea surface temperature (SST) satellite images. Our approach is based on the evaluation and comparison between two unsupervised classification methods, Otsu and Fuzzy C-means, and explores the applicability of these methods to our classification problem. The latter consists in coarse detection of the main thermal front that separates coastal cold upwelling waters from the remaining ocean waters. The algorithm has been applied and validated by an oceanographer over a database of 66 SST images corresponding to southern Moroccan coastal upwelling of the years 2004, 2005, 2007 and 2009. The results indicate that the proposed algorithm revealed is promising and reliable on different upwelling scenarios and for a wide variety of oceanographic conditions.
机译:在这项工作中,我们的目标是使用在海面温度(SST)卫星图像中使用常规方法的自动检测和提取Uppwering领域的自动检测和提取的自动检测和提取算法。 我们的方法是基于两个无监督的分类方法,OTSU和模糊C型方法之间的评估和比较,并探讨了这些方法对我们的分类问题的适用性。 后者在粗糙的热线检测中,从剩下的海水中分离沿海冷藏水域。 该算法已由海洋人应用和验证,在2004年,2005年,2007年和2009年的南部摩洛哥沿海沿海南部的66 SST图像数据库中验证。结果表明,拟议的算法在不同的上升方案方面揭示了很有希望和可靠 以及各种海洋情况。

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