Block-Matching Sub-Pixel Motion Estimation from Noisy, Under-Sampled Frames — An Empirical Performance Evaluation

The performance of block-matching sub-pixel motion estimation algorithms under the adverse conditions of image undersampling and additive noise is studied empirically. This study is motivated by the requirement for reliable subpixel accuracy motion estimates for motion compensated observation models used in multi-frame super-resolution image reconstruction. Idealized test functions which include translational scene motion are defined. These functions are sub-sampled and corrupted with additive noise and used as source data for various block-matching sub-pixel motion estimation techniques. Motion estimates computed from this data are compared with the a-priori known motion which enables an assessment of the performance of the motion estimators considered.