A new method for segmentation of noisy, low-contrast image sequences

We propose a new method for segmenting noisy image sequences in a way that imposes consistency between neighboring segmentations in the sequence. Our method uses a statistical model composed of a spatial Markov random field model and a temporal Markov chain model. Results from segmenting sequences of microscopy images of growing silicon nanowires using the proposed model and method show significant improvement over segmenting the sequences using 2D segmentation.