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首页> 外文会议>Remote Sensing of the Marine Environment; Proceedings of SPIE-The International Society for Optical Engineering; vol.6406 >Textural Analysis for the Detection of Dust Clouds from Infrared Satellite Images
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Textural Analysis for the Detection of Dust Clouds from Infrared Satellite Images

机译：红外卫星图像中尘云检测的纹理分析

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摘要

The remote sensing constitutes a vast field of study whose repercussions are many and varied on environmental management. The phenomenon of dust clouds is a major climatic event in Africa. But the observation means of this phenomenon are still too much limited. The development of an approach consisting in the detection of dust clouds from satellite images can be a solution. In this work, we present a new approach for dust clouds detection in the infrared images coming from the METEOSAT satellite. It is then proved necessary of finding automatic or semi-automatic analysis methods to assist their detection and interpretation. Thus we are interested in image fusion methods for detection structures in the images. In this paper, we present some statistical methods which enable to extract texture features from the images. Then, we describe the method used for selection the best attributes for the images segmentation into three classes: "water clouds", "ocean" and "continent". We then use a method which enable us to segment the class "continent" of the image for dust clouds detection. Finally, we compare our results with another one which shows the zone of presence or absence of dust clouds. This comparison shows that we are in concord because visually, we have a good analogy of shape on the dust clouds zone as well as on the part without dust clouds.
机译：遥感构成了一个广阔的研究领域，其对环境管理的影响是多种多样的。尘云现象是非洲的主要气候事件。但是这种现象的观察手段仍然太有限。一种解决方案是开发一种方法，该方法包括从卫星图像中检测尘云。在这项工作中，我们提出了一种新的方法，用于检测来自METEOSAT卫星的红外图像中的尘埃云。事实证明，有必要寻找自动或半自动分析方法来辅助其检测和解释。因此，我们对用于图像中检测结构的图像融合方法感兴趣。在本文中，我们提出了一些统计方法，这些方法能够从图像中提取纹理特征。然后，我们将用于为图像分割选择最佳属性的方法描述为三类：“水云”，“海洋”和“大陆”。然后，我们使用一种使我们能够对图像的“大陆”进行分类以进行尘云检测的方法。最后，我们将我们的结果与显示尘埃云存在或不存在区域的另一项结果进行比较。这种比较表明我们是一致的，因为在视觉上，我们在尘埃云区域以及没有尘埃云的零件上具有良好的形状比喻。

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