A temporal superresolution method applied to low-light cardiac fluorescence microscopy

In biomicroscopy, fluorescent samples emit very little light, and imaging requires a long camera integration time to acquire an adequate number of photons. However, when imaging live, dynamic biological processes, a long integration time results in motion blur, and a low sampling rate results in temporal aliasing. To reduce these unwanted artifacts, we utilize a temporal superresolution algorithm to reconstruct a high temporal resolution image sequence from multiple low temporal resolution acquisitions. Each acquisition is shifted in time by a subframe delay, and an l₁ cost minimization is used to reconstruct the high temporal resolution sequence. This paper describes the acquisition and reconstruction algorithm, evaluates its performance, and demonstrates its application in live fluorescence bioimaging of the embryonic zebrafish heart. Our temporal superresolution algorithm increases the bandwidth by a factor of 1.5 and shows that temporal super-resolution can be a valuable tool to capture fast dynamic processes in biomicroscopy.