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.
首先探讨了基于提升方案的整数小波变换，结合线性预测技术，提出了一种机载多光谱遥感图像的无损压缩方法。
A new method combining integer wavelet transform and linear prediction technique for lossless compression of airborne multispectral imagery is proposed in this paper.
在数字图像小波多分辨率分析理论基础上，采用小波变换方法对高分辨遥感图像的目标地物边缘进行信息增强，然后与多光谱遥感图像进行特征信息融合。
After the wavelet's multi-resolution analysis, a feature fusion approach was adopted to enhance remote sensing image edge and improve the definition and resolving power of the image.
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