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以ALOS全色波段与多光谱影像为信息源,对几种常用的HIS、PCA、Gram.Schmidt和WAVELET等融合方法进行了比较试验,并通过定性和定量分析对融合效果进行了评价;利用最大似然分类方法,分别对融合前后的影像进行了分类。实验结果表明,小波变换方法在显著提高融合影像空间分辨率的同时,有效保持了多光谱影像的光谱信息,融合效果优于其他融合方法,且分类精度比多光谱影像有较大提高,是监测盐渍地信息提取的有效手段。
By using ALOS panchromatic and multispectral images as the information source, several commonly used fusion methods such as HIS, PCA, Gram.Schmidt and WAVELET were compared and tested, and the fusion effect was evaluated by qualitative and quantitative analysis. Likelihood classification method, the images before and after the fusion were classified. The experimental results show that the wavelet transform method can significantly improve the spatial resolution of the fusion image and effectively preserve the spectral information of the multi-spectral image, and the fusion effect is superior to other fusion methods, and the classification accuracy is greatly improved compared with the multi-spectral image, Effective method of salinization information extraction.