首页> 外文会议>Conference on Image Processing and Pattern Recognition in Remote Sensing Oct 25-27, 2002 Hangzhou, China >Remote Sensing Image Classification Method Using Neural Network Based on Generalized Image
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Remote Sensing Image Classification Method Using Neural Network Based on Generalized Image

机译:基于广义图像的神经网络遥感图像分类方法

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Conventional classification methods cannot recognize the phenomena of "same spectrum with different land matters" so as to degrade classification accuracy. To solve the problem, this paper proposes a new classification method using neural network based on generalized image, where the space information of the image are exploited. Firstly, we combine the original image with its smoothed image to form a binary set called as a "generalized image", which contains the space information of the original image. Secondly, we make use of artificial neural networks (ANN) to train and classify the "generalized image". Finally, we get the classification result of the original image from that of the "generalized image". Experiment results show that the new method is very efficient, and the classification accuracy is improved largely compared with the classic ANN method.
机译:传统的分类方法无法识别“不同地物的光谱相同”的现象,从而降低了分类的准确性。为了解决该问题,本文提出了一种基于神经网络的基于广义图像的分类方法,该方法利用了图像的空间信息。首先,我们将原始图像与其平滑后的图像进行组合,以形成一个称为“广义图像”的二进制集,其中包含原始图像的空间信息。其次,我们利用人工神经网络(ANN)对“广义图像”进行训练和分类。最后,我们从“广义图像”获得原始图像的分类结果。实验结果表明,与传统的人工神经网络方法相比,该方法非常有效,并且分类精度大大提高。

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