Sample Motion for Structured Illumination Fluorescence Microscopy

Structured illumination microscopy (SIM) uses a set of images captured with different patterned illumination to computationally reconstruct resolution beyond the diffraction limit. Here, we propose an alternative approach using a static speckle illumination pattern and relying on inherent sample motion to encode the super-resolved information in multiple raw images, for the case of fluorescence microscopy. From a set of sequentially captured raw images, we jointly estimate the sample motion and the super-resolved image. We demonstrate the feasibility of the proposed method both in simulation and in experiment.

BiPMAP: A Toolbox for Predictions of Perceived Motion Artifacts on Modern Displays

Presenting dynamic scenes without incurring motion artifacts visible to observers requires sustained effort from the display industry. A tool that predicts motion artifacts and simulates artifact elimination through optimizing the display configuration is highly desired to guide the design and manufacture of modern displays. Despite the popular demands, there is no such tool available in the market. In this study, we deliver an interactive toolkit, Binocular Perceived Motion Artifact Predictor (BiPMAP), as an executable file with GPU acceleration. BiPMAP accounts for an extensive collection of user-defined parameters and directly visualizes a variety of motion artifacts by presenting the perceived continuous and sampled moving stimuli side-by-side. For accurate artifact predictions, BiPMAP utilizes a novel model of the human contrast sensitivity function to effectively imitate the frequency modulation of the human visual system. In addition, BiPMAP is capable of deriving various in-plane motion artifacts for 2D displays and depth distortion in 3D stereoscopic displays.