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Information Extraction of High-Resolution Remotely Sensed Image Based on Multiresolution Segmentation

机译：基于多分辨率分割的高分辨率遥感影像信息提取

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The principle of multiresolution segmentation was represented in detail in this study, and the canny algorithm was applied for edge-detection of a remotely sensed image based on this principle. The target image was divided into regions based on object-oriented multiresolution segmentation and edge-detection. Furthermore, object hierarchy was created, and a series of features (water bodies, vegetation, roads, residential areas, bare land and other information) were extracted by the spectral and geometrical features. The results indicate that the edge-detection has a positive effect on multiresolution segmentation, and overall accuracy of information extraction reaches to 94.6% by the confusion matrix.
机译：本研究详细介绍了多分辨率分割的原理，并基于该原理将canny算法应用于遥感图像的边缘检测。基于面向对象的多分辨率分割和边缘检测，将目标图像划分为多个区域。此外，创建了对象层次结构，并通过光谱和几何特征提取了一系列特征（水体，植被，道路，居民区，光秃秃的土地和其他信息）。结果表明，边缘检测对多分辨率分割具有积极的作用，基于混淆矩阵的信息提取总体准确率达到94.6％。

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