Massively Parallel Spatially-Variant Maximum Likelihood Image Restoration

A. Boden, D. Redding, R. Hanisch, J. Mo
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引用次数: 6

Abstract

We consider a massively parallel implementation of Richardson-Lucy or maximum likelihood restoration with a spatially-variant point spread function (PSF). Richardson-Lucy iterates involve the computation of sums of the form: where O(x' q ) is the incident optical field estimate at discrete source location x' q , I(x q ) is the measured discrete image at discrete field location x q , and P(x q , x' q ) is the discrete PSF – the probability that a photon from source region x' q is incident on the detector at field region x q . In general P is a function of source and field coordinates, and the computational burden of Eq. 1 is intractably large.
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大规模并行空间变化最大似然图像恢复
我们考虑了Richardson-Lucy的大规模并行实现或具有空间变异点扩展函数(PSF)的最大似然恢复。Richardson-Lucy迭代涉及计算如下形式的和:其中O(x' q)是在离散源位置x' q处的入射光场估计,I(x q)是在离散场位置x q处测量的离散图像,P(x q, x' q)是离散PSF -来自源区域x' q的光子入射到场区域x q的探测器上的概率。一般来说,P是源坐标和场坐标的函数,并且Eq. 1的计算负担非常大。
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