期刊
IEEE TRANSACTIONS ON IMAGE PROCESSING
卷 21, 期 4, 页码 1863-1873出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TIP.2011.2181528
关键词
Deblurring with spatially variant point spread function (PSF); deconvolution; fluorescence microscopy; L1-regularization; PSF estimation; registration with irregularly placed point markers; tomography; 3-D images
资金
- Excellence Initiative of the German Federal Governments [EXC 294]
- [SFB 592]
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.
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