A low-complexity region-based video compression framework using morphology

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. The cluster motion field is obtained using a novel “cluster matching” approach which is computationally efficient due to the use of only a small cluster “core” that serves as a reliable representative of the entire cluster. A novel morphological dilation operation is used to expand the cluster based on the motion information, and quantization of the cluster motion prediction error is directly incorporated in the region-growing process. Experimental results reveal a 10-30% reduction in coding bit rate over the standard MPEG-1 coder at typical bit rates of 500 kbits/sec to 1 Mb/sec on standard test sequences, while also requiring much lower computational complexity