Abstract

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.

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