Data‐driven, simultaneous blur and image restoration in 3‐D fluorescence microscopy

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Abstract
A novel algorithm for simultaneous blur and image restoration (SBIR)* in three‐dimensional (3‐D) fluorescence microscopy is presented. All the internal parameters including the point spread function essential for the restoration are estimated from the data. Validation of the SBIR algorithm using simulated signals/images and known real world specimens is provided. Both lateral and axial resolution of images are improved by the application of the algorithm. Finally, the results of the application of the algorithm to unknown specimens are shown, demonstrating the potential of the algorithm in practical applications. Furthermore, evidence is provided to show that this algorithm can provide a turn‐key system to deblur images in 3‐D fluorescence microscopy.

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