Region Detection in Sar Images by Adaptive Textural Segmentation

C. Dambra, D. Giusto
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Abstract

A new approach to Synthetic Aperture Radar (SAR) image segmentation based on the use of textural data exploitation is presented. As an efficient way to characterize natural surfaces is to measure their textural features, so a number of textural ("virtual") data are extracted from the original pictures by means of some numerical transformations. The segmentation has been carried out by integrating the hierarchical-clustering and the region-growing approaches into a new technique. Preliminary results on JPL/SAR images are reported and discussed.
基于自适应纹理分割的Sar图像区域检测
提出了一种基于纹理数据挖掘的合成孔径雷达(SAR)图像分割方法。由于测量自然表面的纹理特征是表征自然表面的有效方法,因此通过一些数值变换从原始图像中提取了大量纹理(“虚拟”)数据。将层次聚类和区域增长方法结合为一种新的分割方法。对JPL/SAR图像的初步结果进行了报道和讨论。
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