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。
Hypersperctral remote sensing has two distinct characters that the band number is more than multispectral remote sensing and the width of band is narrow.
波段数目多和波段宽度窄是高光谱分辨率遥感的两个显著特点，常规的用于分析的波段组合方法在信息的利用上是不充分的。
In this paper, we propose an automatic multispectral remote sensing image classification technique based on improved probabilistic diffusion.
为了提高遥感图像分类精度，提出了一种基于概率扩散模型的多光谱遥感图像自动分类技术。
So it is a great progress of remote sensing technology because it can solve many problems which multispectral image cann't solve.
因此，它能解决许多多光谱图像不能解决的问题，是遥感技术应用的一个重大飞跃。
Image acquisition methods are usually flying spot scanners, television cameras (cameras), scanners and remote sensing equipment such as infrared scanners, multispectral scanners.
通常图像获取的方法有飞点扫描器、电视摄像机(摄像头)、扫描仪和遥感设备如红外扫描仪、多光谱扫描仪等。
Image acquisition methods are usually flying spot scanners, television cameras (cameras), scanners and remote sensing equipment such as infrared scanners, multispectral scanners.
通常图像获取的方法有飞点扫描器、电视摄像机(摄像头)、扫描仪和遥感设备如红外扫描仪、多光谱扫描仪等。
应用推荐