Unmixing-based fusion of hyperspectral images with high spatial resolution images

Hyperspectral images having very high spectral resolution are subject to low spatial resolution due to technical constraints. Fusion of hyperspectral images with high resolution multispectral images produces high information-content, high spectral and spatial resolution images. In this study for spatial resolution enhancement of hyperspectral images we propose unmixing-based approaches of fusion with high spatial resolution images. Accordingly; end members extracted out of hyperspectral images are adjusted to multispectral images and they are used to derive high resolution abundances to end up with a fused image. Method is applied on two datasets with hyperspectral and multispectral components as input one being a synthetic and other a real dataset. Method produced better accuracy over conventional methods used in image fusion.