[3L2] [General Session] 2. Machine Learning

[3L2-03] Image Reconstruction for Super Resolution Microscope Using Recursive Bayesian Computation

〇Shunsuke Kido¹, Takashi Washio¹, Tetsuichi Wazawa¹, Takeharu Nagai¹ (1. The Institute of Scientic and Industrial Research, Osaka University)

Keywords:Machine Learning, Recursive Bayesian Computation, Image Reconstruction

We propose to apply Recursive Bayesian Computation to image estimation of SPoD-ExPAN microscopy.The method does not need derivatives of the optimality measure and is supposed to derive images globally better than those of gradient dissent based approaches.In this paper, we present an implementation of the Recursive Bayesian Computation by using Kernel density estimation.Moreover, we introduce regularization to the estimation, and experimentally compare its performance with the case without the regularization.