SPOT6遥感图像融合方法比较研究

Comparative study of image fusion algorithms for SPOT6

SPOT6是2012年法国新发射的遥感卫星,具有空间分辨率高、数据采集能力强等特点,但目前在国土资源监管中,尚未形成完善的SPOT6数据处理技术体系。针对SPOT6卫星图像的特点,借助ENVI,ERDAS和PCI等遥感图像处理软件平台,选取相位恢复(Gram-Schmidt)变换法,高通滤波(HPF)法,超分辨率贝叶斯(Pansharp)法和Pan Sharpening法等4种图像融合方法进行融合对比实验,并从3个方面对融合效果进行了评价:首先对融合结果进行图像质量的定性评价;其次,构建了平均值、标准差、信息熵、平均梯度和相关系数等5个评价指标,对融合效果进行定量评价;最后,借助地物分类精度评价方法,进行了融合后图像的应用效果评价。分析结果表明,对于不同的应用要求,应选择不同的图像融合方法,以期达到最好的应用效果,从而为SPOT6图像在国土资源监管中的应用提供技术支持。

SPOT6 is a new remote sensing satellite launched in 2012 , with the characteristics of high spatial resolution and strong acquisition capability. However, a complete data preprocessing technology for the regulation of land resources has not yet been formed. According to the characteristics of SPOT6 satellite images, four different image fusion methods of Gram - Schmidt, HPF, Pansharp and PanSharpening were selected to conduct the experiment of comparison by using the software platforms of ENVI, ERDAS and PCI. For evaluating the results＆#39;performances, the authors compared them in three aspects. The image quality of experiment results was evaluated qualitatively and also assessed quantitatively by establishing evaluation indexes including mean,standard deviation, information entropy, average gradient and correlation coefficient. The application result of fused images was evaluated based on the evaluation of the classification accuracy. The analytical results show that these algorithms would work in different ways and could be used in different applications. The results achieved by the authors can provide the technical support for application of SPOT6 image to the land resources management.