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Object-Oriented Approach and Texture Analysis for Change Detection in Very High Resolution Images

机译:面向对象的方法和纹理分析用于超高分辨率图像中的变化检测

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The objective of this paper is to develop an object-based change detection method able to qualify the nature of changes in landscapes from remotely sensed images, in terms of geometry and content. The originality of the approach consists in jointly dealing with the analysis of the object contours and the analysis of texture evolution. The method is applied on grassy strips, which are landscape buffers between crops and hydrologic networks. A geometric change index that quantify the intensity of change and that qualify it according its properties is proposed. We also present a content change index that discriminates partial change from diffuse change that affect the object of interest. It turned out that the geometric changes, most of abrupt content changes and some of subtle changes have been accurately detected. Lastly, our approach is suitable on airborne data with a Very High Resolution data and can be generallized to spaceborne images.
机译:本文的目的是开发一种基于对象的变化检测方法,能够在几何和内容方面获得从远程感测图像的景观变化的变化的性质。该方法的原创性包括联合处理对象轮廓的分析和纹理演化分析。该方法应用于草条,其是作物和水文网络之间的景观缓冲。提出了一种量化变化强度的几何变化索引,并提出了根据其属性的限定。我们还提出了一种内容变更索引,其判断影响感兴趣对象的漫反射变化的部分变化。事实证明,几何变化,大多数突然内容的变化和一些细微的变化已经准确地检测到。最后,我们的方法适用于具有非常高分辨率数据的空气传播数据,并且可以通过空间播种图像被混合。

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