ITERATIVE MAXIMUM-LIKELIHOOD DISPLACEMENT FIELD ESTIMATION IN QUANTUM-LIMITED IMAGE SEQUENCES

In this paper, we develop an algorithm for obtaining the maximum likel ihood (ML) estimate of the displacement vector field (DVF) from two co nsecutive image frames of an image sequence acquired under quantum-lim ited conditions, The estimation of the DVF has applications in tempora l filtering, object tracking, stereo matching, and frame registration in low-light level image sequences as well as low-dose clinical x-ray image sequences. In the latter case, a controlled x-ray dosage reducti on may be utilized to lower the radiation exposure to the patient and the medical staff, The quantum-limited effect is modeled as an undesir able, Poisson-distributed, Signal-dependent noise artifact, A Fisher-B ayesian formulation is used in this paper to estimate the DVF and a bl ock component search algorithm is employed in obtaining the solution, Several experiments involving a phantom sequence and a teleconferencin g image sequence with realistic motion demonstrate the effectiveness o f this estimator in obtaining the DVF under severe quantum noise condi tions (20-25 events/pixel).