Detection and Restoration Pipeline for Phase Contrast Microscopy Time Series Images

We propose a pre-processing pipeline for the detection and restoration of distorted frames in phase-contrast microscopy time-series images. The analysis is based on the average intensity values of the frames within any given time-series image. The extent of the correction of intensity variation in frames is determined by the normalization of the difference between the current frame's average intensity and the median of average intensity of all frames. Our restoration algorithm preserves regional trans-passing pixels, does not cause new distortions, and increases the histogram similarity between the distorted and non-distorted frames. The algorithm was validated on 15,395 time-series image frames from 27 experiments and the results were found to be visually and quantitatively accurate.