An edge-preserving MRF model for the detection of missing data in image sequences

This paper proposes a new spatial-temporal Markov random field (MRF) model for the detection of missing data (also referred to as blotches) in image sequences. The blotches in noise-corrupted image sequences exhibit a temporal discontinuity characteristic that is commonly used for the detection of blotches. However, badly motion-compensated pixels also appear as temporal discontinuities, making it difficult to distinguish the true blotches from the poorly motion-compensated regions. The proposed MRF model addresses the problem of incorrect detection due to poor motion compensation at the moving edges. It is found that the degree of incorrect detection (at the moving edges) in image sequences is reduced significantly by incorporating a moving-edge detector into the MRF model.