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The intention for fusion of low-spatial-resolution hyperspectral image (HSI) and high-spatial-resolution multi-spectral image (MSI) is to obtain a high-resolution image in both spectral and spatial domains, which is more suitable for object identification and precise positioning. A novel fusion algorithm for HSI and MSI is proposed in this paper to obtain a better spectral preserving performance....
Spatial resolution is one of the most expensive and hardest to improve in imaging systems. An efficient spatial-spectral data fusion method for superresolution of hyperspectral (HS) imagery through exploiting the spatial correlation of the endmembers using a superresolution mapping (SRM) technique is proposed in this paper. Endmember abundances (fractional images) obtained using linear mixture model...
Hyperspectral technology has introduced a new perspective in remote sensing applications but suffers from low spatial resolution. A new spatial-spectral data fusion technique based on spectral mixture analysis and super-resolution mapping for spatial resolution enhancement of hyperspectral imagery is proposed in this paper. To this end a linear mixture model and a fully constrained least squares based...
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