Simultaneous Temporal Superresolution and Denoising for Cardiac Fluorescence Microscopy

Abstract

Due to low-light emission of fluorescent samples, live fluorescence microscopy imposes a tradeoff between spatio-temporal resolution and signal-to-noise ratio. This can result in images and videos containing motion blur or Poisson-type shot noise, depending on the settings used during acquisition. Here, we propose an algorithm to simultaneously denoise and temporally superresolve movies of repeating microscopic processes that is compatible with any conventional microscopy setup that can achieve imaging at a rate of at least twice that of the fundamental frequency of the process (above 4 frames per second for a 2-Hz process). Our method combines low temporal resolution frames from multiple cycles of a repeating process to reconstruct a denoised, higher temporal resolution image sequence which is the solution to a linear program that maximizes the consistency of the reconstruction with the measurements, under a regularization constraint. This paper describes, in particular, a parallelizable superresolution reconstruction algorithm and demonstrates its application to live cardiac fluorescence microscopy. Using our method, we experimentally show temporal resolution improvement by a factor of 1.6, resulting in a visible reduction of motion blur in both on-sample and off-sample frames.