...键词： 遥感影像分类；纹理特征；影像融合；bp神经网络；灰度共生矩阵 [gap=942]keywords: remote sensing image classification; texture features; fused image; bp neural network; gray level co-occurrence mat..
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Improving classification accuracy is always the focus for remote sensing image classification.
提高遥感图像分类精度一直是受到普遍关注的焦点问题。
Texture analysis has become an important means for improving the accuracy of remote sensing image classification.
纹理分析是提高遥感影像分类精度的重要手段之一。
Current remote sensing image classification models and algorithms commonly used statistical methods, neural networks, Bayesian and so on.
目前遥感影像分类的常用模型和算法有统计学方法、神经网络、贝叶斯等。
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