Image processing metrics for phase identification of a multiaxis MEMS scanner used in single pixel imaging

This paper applies image processing metrics to tracking of perturbations in mechanical phase delay in a multi-axis microelectromechanical system (MEMS) scanner. The compact mirror is designed to scan a laser beam in a Lissajous pattern during the collection of endoscopic confocal fluorescence images, but environmental perturbations to the mirror dynamics can lead to image registration errors and blurry images. A binarized, threshold-based blur metric and variance-based sharpness metric are introduced for detecting scanner phase delay. Accuracy of local optima of the metric for identification of phase delay is examined, and relative advantages for processing accuracy and computational complexity are assessed. Image reconstruction is demonstrated using both generic images and sample tissue images, with significant improvement in image quality for tissue imaging. Implications of non-ideal Lissajous scan effects on phase detection and image reconstruction are discussed.