Superresolution reconstruction of hyperspectral images

Hyperspectral images are used for aerial and space imagery applications including target detection, tracking, agricultural and natural resource exploration. Unfortunately, atmospheric scattering, secondary illumination, changing viewing angles and sensor noise degrade the quality of these images. We introduce a novel superresolution reconstruction method for hyperspectral images. An integral part of our work is to model the hyperspectral image acquisition process. We propose a model that enables us to represent the hyperspectral observations from different wavelengths as weighted linear combinations of a small number of basis image planes. Then a method for applying superresolution to hyperspectral images using this model is presented. The method fuses information from multiple observations and spectral bands to improve spatial resolution and reconstruct the spectrum of the observed scene.