A low-complexity region-based video coder using backward morphological motion field segmentation

We introduce a novel region-based video compression framework based on morphology to efficiently capture motion correspondences between consecutive frames in an image sequence. Our coder is built on the observation that the motion field associated with typical image sequences can be segmented into component motion subfield “clusters” associated with distinct objects or regions in the scene, and further, that these clusters can be efficiently captured using morphological operators in a “backward” framework that avoids the need to send region shape information. Region segmentation is performed directly on the motion field by introducing a small “core” for each cluster that captures the essential features of the cluster and reliably represents its motion behavior. Cluster matching is used in lieu of the conventional block matching methods of standard video coders to define a cluster motion representation paradigm. Furthermore, a region-based pel-recursive approach is applied to find the refinement motion field for each cluster and the cluster motion prediction error image is coded by a novel adaptive scalar quantization method. Experimental results reveal a 10-20% reduction in prediction error energy and 1-3 dB gain in the final reconstructed peak signal-to-noise ratio (PSNR) over the standard MPEG-1 coder at typical bit rates of 500 Kb/s to 1 Mb/s on standard test sequences, while also requiring lower computational complexity