Long-Term Memory Prediction Using Affine Motion Compensation

Long-term memory prediction extends motion compensation from the previous frame to several past frames with the result of increased coding efficiency. In this paper we demonstrate that combining long-term memory prediction with affine motion compensation leads to further coding gains. For that, various affine motion parameter sets are estimated between frames in the long-term memory buffer and the current frame. Motion compensation is conducted using standard block matching in the multiple reference frame buffer. The picture reference and the affine motion parameters are transmitted as side information. The technique is embedded into a hybrid video coder mainly following the H.263 standard. The coder control employs Lagrangian optimization for the motion estimation and macroblock mode decision. Significant bit-rate savings between 20 and 50 % are achieved for the sequences tested over TMN-10, the test model of H.263+. These bit-rate savings correspond to gains in PSNR between 0.8 and 3 dB.