Abstract

Sparse representation is commonly used in correction models to reduce thermal radiation effects. If the correction problem is restricted to a sparse representation problem, residual aero-optic thermal radiation effects will appear in the corrected results. To accurately estimate the thermal radiation bias field, the low-frequency information of the thermal radiation bias field is explored. We propose a correction model to integrate the low-frequency constraint on the thermal bias field and gradient sparse constraint on the latent clear image. A split Bregman alternating iterative algorithm is used to solve the minimization problem of the correction model. The experimental results show that the proposed method can effectively remove thermal radiation effects and greatly improve image quality for infrared focal plane detection.

© 2019 Optical Society of America

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