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Segmentation method based on multiobjective optimization for very high spatial resolution satellite images

机译:基于多目标优化的超高分辨率卫星图像分割方法

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In this paper, a new multicriterion segmentation method has been proposed to be applied to satellite image of very high spatial resolution (VHSR). It is consisted of the following process: For each region of the grayscale image, a center of gravity has been calculated and it has been also selected a threshold for its histogram. According to a certain criteria, this approach has been based on the separation of the different classes of grayscale in an optimal way. The proposed approach has been tested on synthetic images, and then has applied to an urban environment for the classification of data in Quickbird images. The selected zone of study has been laid in Skhirate-Témara province, northwest of Morocco. Which is based on the Levine and Nazif criterion, this segmentation technique has given promising results compared those obtained using OTSU and K-means methods.
机译:本文提出了一种新的多准则分割方法,将其应用于空间分辨率非常高的卫星图像。它由以下过程组成:对于灰度图像的每个区域,已经计算了重心,并且还为其直方图选择了阈值。根据某些标准,该方法基于以最佳方式分离不同类别的灰度的方法。所提出的方法已经在合成图像上进行了测试,然后应用于快速鸟图像中数据分类的城市环境。选定的研究区域位于摩洛哥西北部的Skhirate-Témara省。基于Levine和Nazif准则,与使用OTSU和K-means方法获得的分割结果相比,该分割技术已给出了可喜的结果。

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