Fast hyperspectral cube reconstruction for a double disperser imager
Abstract
We consider the problem of hyperspectral cube reconstruction with a new controllable imaging system. The reconstruction with a small number of images acquired with different configurations of the imager avoids a complete scanning of the hyperspectral cube. We focus here on a quadratic penalty reconstruction approach, which provides a fast resolution thanks to the high sparsity of the involved matrices. While such a regu-larization is known to smooth the restored images, we propose to exploit the system capability to acquire the panchromatic image of the scene, to introduce prior information on the sharp edges of the image, leading to a fast and edge-preserved reconstruction of the image.
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