Abstract
Unlike multispectral (MSI) and panchromatic (PAN) images, the spatial resolution of hyperspectral images (HSI) is limited. In many applications, HSI with a high spectral as well as spatial resolution are required. In this paper, a new method for superresolution of HSI is introduced. A high resolution HSI (HRHSI) is constructed by using the linear spectral unmixing model and making use of a MSI of the same scene. As a regularization, we apply a sparse representation of the HSI, obtained by constructing a dictionary of unrelated PAN images. Experiments show that the reconstruction quality is higher than some the well-known HSI spatial resolution enhancement methods.
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