Lateral drift correction in time-laps images by the particle-tracking algorithm

Postrecording Pixel-Reconstruction Approach for Correcting the Lateral Drifts in Surface Plasmon Resonance Microscope

Surface plasmon resonance microscope (SPRM) sample stage inevitably suffers from lateral drifts as a result of many environmental factors including thermal fluctuation, mechanical vibration, and relaxation. It places great obstacles to time-lapsed imaging and measurements that need high spatial resolution or long recording time. Existing solutions often require experimental efforts such as the addition of optical markers together with piezoelectric stage-based active feedback configurations. Herein, we propose an all-digital, postrecording image-processing method to remove the lateral drift in a series of time-lapsed SPRM images. The method first calculates the value of lateral drift at subpixel accuracy by combining image cross-correlation analysis and superlocalization strategy. It subsequently reconstructed the drift-free image sequences in a pixel-by-pixel and frame-by-frame manner, according to the linear decomposition and reconstruction principle. This method purely relies on image processing, and it does not require any experimental efforts or hardware. In addition to SPRM, we further demonstrated the applicability of the present method in other types of optical imaging techniques including bright-field transmission microscope and dark-field scattering microscope.

Drift estimation for single marker switching based imaging schemes

In recent years, the diffraction barrier in fluorescence imaging has been broken and optical nanoscopes now routinely image with resolutions of down to 20 nm, an improvement of more than 10 fold. Because this allows imaging much smaller features and because all super-resolution approaches trade off speed for spatial resolution, mechanical instabilities of the microscopes become a limiting factor. Here, we propose a fully data-driven statistical registration method for drift detection and drift correction for single marker switching (SMS) imaging schemes, including a guideline for parameter choice and quality checks of the drift analysis. The necessary assumptions about the drift are minimal, allowing a model-free approach, but more specific models can easily be integrated. We determine the resulting performance on standard SMS measurements and show that the drift determination can be routinely brought to the range of precision achievable by fiducial marker-tracking methods.