Anisotropic Total Variation Regularization Based NAS-RIF Blind Restoration Method for OCT Image

Xuesong Fu, Jianlin Wang, Zhixiong Hu, Yongqi Guo, Kepeng Qiu, Rutong Wang
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引用次数: 1

Abstract

Based on anisotropic total variation regularization (ATVR), a nonnegativity and support constraints recursive inverse filtering(NAS-RIF) blind restoration method is proposed to enhance the quality of optical coherence tomography (OCT) image. First, ATVR is introduced into the cost function of NAS-RIF to improve the noise robustness and retain the details in the image. Since the split Bregman iterative is used to optimize the ATVR based cost function, the ATVR based NAS-RIF blind restoration method is then constructed. Furthermore, combined with the geometric nonlinear diffusion filter and the Poisson-distribution-based minimum error thresholding, the ATVR based NAS-RIF blind restoration method is used to realize the blind OCT image restoration. The experimental results demonstrate that the ATVR based NAS-RIF blind restoration method can successfully retain the details in the OCT images. In addition, the signal-to-noise ratio of the blind restored OCT images can be improved, along with the noise robustness.
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基于各向异性全变分正则化的OCT图像NAS-RIF盲恢复方法
为了提高光学相干层析成像(OCT)图像的质量,提出了一种基于各向异性全变差正则化(ATVR)的非负性支持约束递推反滤波(NAS-RIF)盲恢复方法。首先,将ATVR引入到NAS-RIF的代价函数中,提高噪声鲁棒性并保留图像中的细节;由于采用分裂Bregman迭代对基于ATVR的代价函数进行优化,因此构造了基于ATVR的NAS-RIF盲恢复方法。结合几何非线性扩散滤波和基于泊松分布的最小误差阈值分割,采用基于ATVR的NAS-RIF盲恢复方法实现了OCT图像的盲恢复。实验结果表明,基于ATVR的NAS-RIF盲恢复方法能够很好地保留OCT图像中的细节。此外,盲恢复OCT图像的信噪比可以得到提高,噪声的鲁棒性也得到提高。
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