An adaptive statistical method for denoising 4D fluorescence image sequences with preservation of spatio-temporal discontinuities

We present a spatio-temporal filtering method for significantly increasing the signal-to-noise ratio in noisy fluorescence microscopic image sequences where small particles have to be tracked from frame to frame. Image sequences restoration is achieved using a spatio-temporal adaptive window approach with an appropriate on-line window geometry specification. We have applied this method to noisy synthetic and real 3D image sequences where a large number of small fluorescently labelled vesicles are moving in regions close to the Golgi apparatus. The SNR is shown to be drastically improved and the enhanced vesicles can be segmented. This novel approach can be further used for biological studies where the dynamic of small objects of interest has to be analyzed in molecular and sub-cellular bio-imaging.