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Remote sensing image fusion based on sparse representation support set

MA Donglei;DING Jianwei;TAN Kun;China University of Mining and Technology;The Second Surveying and Mapping Institute of Hebei Province;  
For the common sparse representation coefficient fusion rule cannot completely retain the useful information of two images,this paper proposes a new sparse representation coefficient fusion rule by analyzing the spatial distribution of sparse representation coefficient support set space.Firstly,the generalized IHS transform is applied to multispectral images,and the brightness components and panchromatic images are respectively sparse representation.Secondly,the support set of the brightness component and panchromatic image sparse representation solution is analyzed,and the sparse representation coefficients corresponding to the support set intersection and the difference the sections of the literary collections are respectively used to fuse with the L1 norm.Finally,the weighted detail insertion method is used to insert the fused luminance component details into multispectral images,and the high resolution multispectral image is obtained.The experimental results show that the method can improve the spatial resolution and reduce spectral loss.In the subjective visual and objective evaluation,more than the commonly used fusion rules methods.
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