Multiview Deblurring for 3-D Images from Light-Sheet-Based Fluorescence Microscopy
Multiview Deblurring for 3-D Images from Light-Sheet-Based Fluorescence Microscopy
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DOI：
10.1109/tip.2011.2181528
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发表时间：
2012-04-01
影响因子：
10.6
通讯作者：
Burkhardt, Hans
中科院分区：
文献类型：
--
作者：
Temerinac-Ott, Maja;Ronneberger, Olaf;Burkhardt, Hans
提出了一种基于空间变化点扩散函数的三维多视点图像去模糊算法。将该算法应用于体显微图像的多视图重建。它包括使用不规则放置的点标记（珠子）配准和估计PSF。我们制定多视图去模糊作为一个能量最小化问题的L1正则化。优化是基于正则化的Lucy-Richardson算法，我们扩展到处理我们更一般的模型。通过在现实训练集上优化模型参数，以深刻的方式选择模型参数。我们定量和定性地与现有的方法进行比较，并表明，我们的方法提供了更好的信噪比，提高了重建图像的分辨率。
We propose an algorithm for 3-D multiview deblurring using spatially variant point spread functions (PSFs). The algorithm is applied to multiview reconstruction of volumetric microscopy images. It includes registration and estimation of the PSFs using irregularly placed point markers (beads). We formulate multiview deblurring as an energy minimization problem subject to L1-regularization. Optimization is based on the regularized Lucy-Richardson algorithm, which we extend to deal with our more general model. The model parameters are chosen in a profound way by optimizing them on a realistic training set. We quantitatively and qualitatively compare with existing methods and show that our method provides better signal-to-noise ratio and increases the resolution of the reconstructed images.