Segmentation-based video coding

Low bit rate video coding is gaining attention through a current wave of consumer oriented multimedia applications which aim, e.g., for video conferencing over telephone lines or for wireless communication. In this work we describe a new segmentation-based approach to video coding which belongs to a class of paradigms appearing very promising among the various proposed methods. Our method uses a nonlinear measure of local variance to identify the smooth areas in an image in a more indicative and robust fashion: First, the local minima in the variance image are identified. These minima then serve as seeds for the segmentation of the image with a watershed algorithm. Regions and their contours are extracted. Motion compensation is used to predict the change of regions between previous frames and the current frame. The error signal is then quantized. To reduce the number of regions and contours, we use the motion information to assist the segmentation process, to merge regions, resulting in a further reduction in bit rate. Our scheme has been tested and good results have been obtained.