在颜色科学领域，数码相机被广泛地用于颜色测量、多光谱图像的颜色复制、光谱重建和产品检测、分类等场合。
In color science field, digital still cameras have be widely used for color measurement, multispectral imaging color reproduction, spectral reconstruction and production classifying etc.
本论文研究利用多光谱图像进行自然地物目标分类技术。
The aim of this paper is to study classification approach of topographical objects with Multi-spectral image.
通过高几何分辨率图像与多光谱波段融合方法可以，增强变化信息，纹理特征参与变化信息提取可以提高变化类型的分类精度。
It is concluded that the fusion of high spatial imagery and multi-spectral bands can enhance change information, and the fusion of texture character can improve the classification results.
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。
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。
In this paper, we propose an automatic multispectral remote sensing image classification technique based on improved probabilistic diffusion.
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