VectorFist / Cnn Fusion
采用CNN将高分辨率灰度图像和低分辨率彩色图像合成为高分辨率彩色图像的图像融合算法
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FusionCNN
此仓库为论文 FusionCNN: a remote sensing image fusion algorithm based on deep convolutional neural networks 的开源实现。论文中提出了一种新颖的遥感图像融合算法，这种方法能够很好的保留多光谱图像的光谱信息和全色图像的空间信息。
实验图像
image 1
ms image
pan image
fusion image
image 2
ms image
pan image
fusion image
实验说明
训练模型
train.py用于训练模型，其中可以指定一些必要的训练参数。
对于使用的cifar数据集，需要在cifar_data_hls.py中read_data_sets中指定数据集目录。
测试模型
evaluate.py用于在测试集上评估训练好的模型。
融合图像
fusion.py中使用训练好的模型来融合遥感图像。
仓库中已经提供了一个训练好的模型，你可直接使用，可以直接运行次脚本。
如论文中所述，为了获得更好的融合质量，需要在融合之前将Pan图像进行必要的预处理（非必须），也即使用NSCT算法来对Pan进行增强，这一部分处理在matlab中进行，详细做法见论文。
模型的输入即为Pan图像（或增强后的Pan图像）和MS图像，只需指定pan_path、ms_path和save_path即可。
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