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- W2379786051 abstract "Fusion of images with different spatial resolution can improve visualization of the images involved.This study tried to show that the fusion of the images could improve classification accuracy of the images.Three image fusion algorithms were employed in the study of data fusion and classification of ALOS panchromatic and multi-spectral images,taking the center part of Yancheng city as the study area.These were Brovey transform,High Pass Filter(HPF) and Gram-Schmidt(GS) methods,the effectiveness of each algorithm was evaluated based on qualitative evaluation and classification accuracy.The result showed that the GS transform was the best method in retaining spectral information of original image,which did not cause spectral distortion,and achieving the highest classification accuracy.Brovey-fused image had higher classification accuracy but significantly lost spectral properties of the original image.HPF-fused image retained spectral information of original image but had the lowest classification accuracy.Simultaneously,classification accuracy varies in different surface features.In short,the GS transform is the best method compared with the other two methods." @default.
- W2379786051 created "2016-06-24" @default.
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- W2379786051 date "2012-01-01" @default.
- W2379786051 modified "2023-09-26" @default.
- W2379786051 title "Land Cover Classification Based on ALOS Panchromatic and Multispectral Images Fusion" @default.
- W2379786051 hasPublicationYear "2012" @default.
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