A Nonuniform Correction Algorithm Based on Regularization Constraints of Gaussian Surface Fitting

Ruzhou Li, Yu Shi, Zhigao Huang
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引用次数: 0

Abstract

Due to the limitation of hardware, infrared optical systems often have thermal radiation noise effects on the acquired images. Although the effect of thermal radiation on image quality can be reduced with proper optical design, it is expensive and cannot completely eliminate the effect of thermal radiation. To solve this problem, for the purpose of improving the image quality after imaging, we propose a novel image non-uniformity correction method. The optical head cover of the imaging system is usually semi-circular, and the thermal radiation effect conforms to the Gaussian distribution. Therefore, this paper firstly preprocesses the degraded image, including Gaussian surface fitting and image layering, and then introduces the preprocessing results into In the correction model, frame wave regularization constraints are imposed on the potential clear images, and the Gaussian surface fitting regularization term is introduced into the thermal radiation correction model, and the clear images and thermal radiation effect maps are estimated by Split Bregman iterative optimization. The experimental results show that our proposed method can perform the non-uniform correction caused by thermal radiation noise well.
基于正则化约束的高斯曲面拟合非均匀校正算法
由于硬件的限制,红外光学系统通常会对获取的图像产生热辐射噪声影响。虽然通过适当的光学设计可以降低热辐射对图像质量的影响,但它的成本很高,不能完全消除热辐射的影响。为了解决这一问题,以提高成像后的图像质量为目的,我们提出了一种新的图像非均匀性校正方法。成像系统的光学罩通常为半圆形,热辐射效应符合高斯分布。因此,本文首先对退化图像进行预处理,包括高斯曲面拟合和图像分层,然后将预处理结果引入到校正模型中,对潜在的清晰图像施加帧波正则化约束,并将高斯曲面拟合正则化项引入到热辐射校正模型中,通过Split Bregman迭代优化对清晰图像和热辐射效应图进行估计。实验结果表明,该方法能很好地解决热辐射噪声引起的非均匀校正问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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