Abstract
Long-wave infrared (LWIR) images have important applications in retrieving land surface temperature. However, LWIR images are often inevitably suffered from stripe noise, a special type of spatial domain fixed pattern noise. This paper proposes a novel spectral separation algorithm for LWIR image destriping. Specifically, since the mid-wave infrared (MWIR) bands contain both radiant and reflective energy, we use MWIR as reference images to remove the stripe noise in the LWIR bands. We formulate the spectral separation problem as a convex optimization problem, where the difference between LWIR and the radiant component of MWIR, and the difference between the visible and near infrared (VNIR) image and the reflective component of MWIR are regularized to exploit the similarities between the corresponding bands. The obtained radiant component is then utilized to recover the LWIR band. Experimental results using Gaofen-5 datasets demonstrate that the proposed algorithm has good performance in removing the stripe noise.
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