基于纹理分割的神经网络云检测方法

A. Visa, K. Valkealahti, O. Simula
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引用次数: 30

摘要

介绍了一种从遥感图像中检测和识别云的新方法。云的检测和识别是基于纹理的。图像被划分为纹理均匀的区域,这些纹理的解释是基于纹理映射。该地图是通过人工神经网络方法创建的。神经网络方法的使用使得应用无监督学习范式来连续训练地图成为可能。纹理映射是通过特征向量的自组织过程生成的。这是以一种无监督的方式进行的。标签是通过监督过程实现的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Cloud detection based on texture segmentation by neural network methods
A novel method to detect and recognize clouds from remote sensing images is introduced. The detection and recognition of clouds are based on textures. The images are partitioned into homogeneously textured regions, and the interpretation of those textures is based on a texture map. This map is created by means of artificial neural network methodology. The use of neural network methods makes it possible to apply an unsupervised learning paradigm to train the map continuously. The texture map is created by a self-organizing process of feature vectors. This is performed in an unsupervised way. The labeling is achieved by a supervised process.<>
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