ADAPTIVE CODING OF MOVING-OBJECTS FOR VERY-LOW BIT RATES

This paper describes an object-based video coding system with new idea s in both the motion analysis and source encoding procedures. The movi ng objects in a video are extracted by means of a joint motion estimat ion and segmentation algorithm based on the Markov random field (MRF) model. The two important features of the presented technique are the t emporal Linking of the objects, and the guidance of the motion segment ation with spatial color information. This facilitates several aspects of an object-based coder, First, a new temporal updating scheme great ly reduces the bit rate to code the object boundaries without resortin g to crude lossy approximations. Next, the uncovered regions can be ex tracted and encoded in an efficient manner by observing their revealed contents. The objects are classified adaptively as P objects or I obj ects and encoded accordingly, Subband/wavelet coding is applied in enc oding the object interiors, Simulations at very low bit rates yielded comparable performance in terms of reconstructed PSNR to the H.263 cod er. The object-based coder produced visually more pleasing video with less blurriness and devoid of block artifacts, thus confirming the adv antages of object-based coding at very low bit-rates.