Optical remote sensing relies on the use of panchromatic, multispectral and hyperspectral images with a high spectral resolution and spatial resolution to distinguish the observed scene.
光学遥感依赖于利用多光谱和超光谱图像具有较高的光谱分辨率和空间分辨率来对所观测场景进行辨别。
The experiments of the recognition of various types of water bodies on the satellite image prove this recognizing method is feasible with high spatial resolution satellite images.
在区域分割与边界跟踪基础上，对卫星图像进行水体形状特征的抽取与描述，实现不同水体类型的识别。
BP neural network is used to reconstruct a high spatial resolution remote sensed image from low spatial resolution images sequences.
介绍了一种利用BP神经网络由低空间分辨率遥感图像序列重建得到一幅较高空间分辨率图像的算法。
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