Image segmentation is the important content in digital image processing, remote image segmentation is the one of important application aspect of image segmentation.
图像分割是数字图像处理领域中的重要内容，遥感图像分割是图像分割的一个重要应用方向。
This dissertation has studied the segmentation method of remote sensing image based on multiscale edge, based on wavelet, invariant moment and the edge detection technique of remote sensing image.
本文以小波分析、不变矩等数学理论和遥感图像边缘检测技术为研究背景，较深入地进行了遥感图像多尺度边缘分割的方法研究。
Image segmentation is one of the basic technologies in remote sensing and medical image processing but it lacks current algorithm for engineering applications.
图像分割是遥感和医学图像处理的基础技术之一，但是目前缺乏工程化通用算法。
Image segmentation brings errors in low or medium-resolution remote sensing images because a single pixel covers a larger area and there are a lot of mixed pixels.
对于中、低分辨率遥感图像来说，单个像元的面积较大，且混合像元现象严重，图像分割会产生较大的误差。
Experiments show that this method not only guarantees the accuracy of the segmentation, but also achieved fast segmentation of remote sensing image.
多幅遥感图像分割实验证明该方法在保证精度的情况下能有效的减少计算量，实现了遥感图像的快速分割。
The issues such as image correspondence, clustering, segmentation and vectorization involved in remote sensing are discussed.
完成了遥感图像配准、聚类、分割和向量化等功能。
We provided a new method of remote sensing image multiscale edge segmentation based on invariant moment.
面对海量遥感数据，准确、高效的分割方法是必须的，因此提出了遥感图像多尺度边缘分割的方法。
Aiming at the problem of poor real-time ability of graph cut, this paper suggests a remote sensing image segmentation approach based on quarter-tree and graph cut.
针对图割算法实时性差的问题，提出一种基于四叉树与图割的遥感图像分割方法。
Aiming at the problem of poor real-time ability of graph cut, this paper suggests a remote sensing image segmentation approach based on quarter-tree and graph cut.
针对图割算法实时性差的问题，提出一种基于四叉树与图割的遥感图像分割方法。
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