宽视场偏振调制成像的变指数正则化重构方法

Reconstruction of Variable Exponential Regularization for Wide-Field Polarization-Modulated Imaging

提出了一种针对宽视场偏振调制显微成像的顾及多降晰因素的点扩展函数(PSF)估计与图像重构的正则化方法,对降晰过程中图像因偏振角调制曲线的拟合偏差、光学系统退化和电荷耦合器件(CCD)离散欠采样而退化的PSF估计选用了自适应的变指数函数正则化模型,充分利用获取的图像内容特性选用可变的正则化范数,有效抑制了全变分(TV)正则化的阶梯效应和Tikhonov正则化保边性差的缺点。求解过程采用了优化的Split-Bregman迭代算法,在保证估计精度的同时降低了计算复杂度。实验结果表明,本文提出的方法能有效估计出成像退化的PSF,重建的噪声鲁棒性更好。

In this study,a regularization method of point spread function(PSF)estimation and image reconstruction considering multiple blur factors about image degradation is proposed for wide-field polarization-modulated microscopic imaging.The adaptive regularization model of variable exponential function is used for the PSF estimation,which is degraded due to the fitting deviation of polarization-angle modulation curve,the degradation of optical system,and discrete under-sampling of charge-coupled device(CCD)during the blurring process.The aim is to fully utilize the acquired image content features,adaptively select a variable regularization norm,and effectively restrain the staircase effect of total variation regularization and the disadvantage of poor edge-preserving property of Tikhonov regularization.The optimized Split-Bregman iterative algorithm is adopted in the solution process,which can ensure the estimation accuracy and reduce the computational complexity as well.Experimental results show that the proposed method can effectively estimate the degraded PSF and improve the noise robustness of image reconstruction.