Deconvolution Algorithms for Fluorescence and Electron Microscopy

DECONVOLUTION ALGORITHMS FOR FLUORESCENCE AND ELECTRONMICROSCOPY bySiddharth Shah Chair: Andrew E. Yagle In many imaging applications the image formation process is influenced by thedevice physics of the imaging system. As a result, the image is a distorted version ofthe object. This distortion effect, mathematically modeled as the transfer function,ultimately limits the resolution of the imaging system. In a high-resolution imag-ing system, this limitation needs to be overcome either by improving the imaginghardware or by computational post-processing of the image. Deconvolution refers tothe class of computational methods that aim to improve the resolution of the ob-served image by reversing the effect of the transfer function. The focus of this thesisis in the development and deployment of deconvolution algorithms for microscopyapplications.The first part of this thesis discusses two novel deconvolution algorithms thathave been developed from a deterministic approach. The key feature of both the