Comparative study of image fusion algorithms for SPOT6
GUO Lei1, YANG Jihong2, SHI Liangshu2, ZHAN Ying2, ZHAO Dongling1, ZHANG Chao1, SUN Jiabo1, JI Jiajia1
1. College of Information and Electrical Engineering, China Agricultural University, Beijing 100083, China;
2. China Land Surveying and Planning Institute, Ministry of Land and Resources, Beijing 100035, China
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' 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.
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2014, Vol. 26 
