Semi-Blind Spatially-Variant Deconvolution in Optical Microscopy with Local Point Spread Function Estimation by Use of Convolutional Neural Networks

Adrian Shajkofci, Michael Liebling
2018 2018 25th IEEE International Conference on Image Processing (ICIP)  
We present a semi-blind, spatially-variant deconvolution technique aimed at optical microscopy that combines a local estimation step of the point spread function (PSF) and deconvolution using a spatially variant, regularized Richardson-Lucy algorithm. To find the local PSF map in a computationally tractable way, we train a convolutional neural network to perform regression of an optical parametric model on synthetically blurred image patches. We deconvolved both synthetic and
more » ... ired data, and achieved an improvement of image SNR of 1.00 dB on average, compared to other deconvolution algorithms.
doi:10.1109/icip.2018.8451736 dblp:conf/icip/ShajkofciL18 fatcat:apvlnr7nufbctiapvyz3fz3byu