Fourier ptychographic reconstruction using Poisson maximum likelihood and truncated Wirtinger gradient

• DOI: 10.1038/srep27384
• Publication Date: 2016-06-10T09:38:49Z
• Authors: Liheng Bian; Jinli Suo; Jaebum Chung; Xiaoze Ou; Changhuei Yang; Feng Chen; Qionghai Dai
• Keywords: FOS: Computer and information sciences; Computer Vision and Pattern Recognition (cs.CV); Computer Science - Computer Vision and Pattern Recognition; 0202 electrical engineering, electronic engineering, information engineering; FOS: Physical sciences; 02 engineering and technology; 530; Article; Physics - Optics; Optics (physics.optics)

Abstract Fourier ptychographic microscopy (FPM) is a novel computational coherent imaging technique for high space-bandwidth product imaging. Mathematically, (FP) reconstruction can be implemented as phase retrieval optimization process, in which we only obtain low resolution intensity images corresponding to the sub-bands of sample’s (HR) spatial spectrum and aim retrieve complex HR spectrum. In real setups, measurements always suffer from various degenerations such Gaussian noise, Poisson speckle noise pupil location error, would largely degrade reconstruction. To efficiently address these degenerations, propose FP method under gradient descent framework this paper. The utilizes maximum likelihood better signal modeling truncated Wirtinger effective error removal. Results on both simulated data captured using our laser-illuminated FPM setup show that proposed outperforms other state-of-the-art algorithms. Also, have released source code non-commercial use.