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通过ℓ正则化最小化实现气动热图像的强度非均匀性校正。

Intensity non-uniformity correction of aerothermal images via ℓ-regularized minimization.

作者信息

Liu Li, Zhang Tianxu

出版信息

J Opt Soc Am A Opt Image Sci Vis. 2016 Nov 1;33(11):2206-2212. doi: 10.1364/JOSAA.33.002206.

Abstract

Aerothermal-induced intensity non-uniformity (NU) effects severely influence the effective performance of infrared (IR) imaging systems in high-speed flight. In this paper we propose a ℓ-regularized minimization method to remove intensity NU in IR images. Different from the existing NU correction methods, we consider and study important priors from the NU noise and the IR image, respectively. We assume spatial smoothness of the NU noise and piecewise continuity of the IR image, where the ℓ regularization term is employed in the correction model. A computationally efficient numerical algorithm based on half-quadratic regularization is adopted to solve the optimization problem. To tackle the non-convex ℓ-norm minimization sub-problem in this scheme, a generalized iterated shrinkage algorithm is used. Significant improvement on the image quality is obtained on both simulation and experimental studies. Both quantitative and qualitative comparisons to specialized state-of-the-art algorithms demonstrate its superiority.

摘要

气动热诱导强度不均匀性(NU)效应严重影响高速飞行中红外(IR)成像系统的有效性能。本文提出一种ℓ正则化最小化方法来去除红外图像中的强度NU。与现有的NU校正方法不同,我们分别考虑并研究了来自NU噪声和红外图像的重要先验信息。我们假设NU噪声的空间平滑性和红外图像的分段连续性,在校正模型中采用ℓ正则化项。采用基于半二次正则化的高效数值算法来求解优化问题。为了解决该方案中的非凸ℓ范数最小化子问题,使用了广义迭代收缩算法。在模拟和实验研究中均获得了图像质量的显著改善。与专门的先进算法进行的定量和定性比较都证明了其优越性。

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