A Bayes decision test for detecting uncovered-background and moving pixels in image sequences

摘要

We present a ternary hypothesis test for the detection of stationary, moving, and uncovered-background pixels between two image frames in a noisy image sequence using the Bayes decision criterion. Unlike many uncovered-background detection schemes, our scheme does not require motion estimation for the differentiation between moving pixels and uncovered-background pixels. We formulate the Bayes decision rule using a single intensity-difference measurement at each pixel and using multiple intensity-difference measurements in the neighborhood of each pixel. We quantitatively evaluate our detection algorithm on an image sequence which we have generated and qualitatively on the Trevor White image sequence.