Multi-temporal approach to atmospheric effects compensation in hyperspectral image classification

This paper presents a multi-temporal approach to compensate the atmospheric effects in spaceborne hyperspectral images. It focuses on applications where a hyperspectral sensor periodically acquires images of the same scene and such images have to be classified. The method assumes that a reference reflectance image of the region of interest, equipped with an accurate classification map, is available. Such an image and the corresponding classification map represent the database that will be a reference for the classification of temporally subsequent images over the same scene. The multi-temporal approach allows the classification to be performed on at sensor radiance data and it does not require the knowledge of the atmospheric conditions at the acquisition time.