Spatial and spectral coordinate super resolution of hyperspectral imagery based on redundant dictionary

Hyperspectral imagery has been widely used in various fields for its rich amount of feature information. The quality of hyperspectral imagery has been set higher requirements. As a result of the limitation of imaging semiconductor technology, hyperspectral image resolution needs to be improved by a signal processing method. This paper presents a recovery algorithm of spatial and spectral coordinate super-resolution of hyperspectral image based on redundant dictionary. Compared with the traditional image super-resolution restoration algorithm, the super-resolution restoration in the spectral of hyperspectral image was added on the basis of spatial resolution improvement. The original constraint was added in the algorithm and edges of reconstructed image were sharpened with the Maximum a Posterior. The results show this algorithm can effectively improve spatial and spectral resolution of the hyperspectral imagery.