Content-based hybrid DPCM/classified vector quantization for coding video telephony sequences

A novel hybrid DPCM/CVQ (classified vector quantization) method is proposed to encode and decode video telephony sequences. The CVQ coding method is b ased on the detection of human faces within a video signal. This detection will improve three aspects of video coding efficiency. First, knowledge of the image content carl be used to remove coding redundancy within the predi ction en or. Second, selective coding can be adopted to further reduce psyc ho-visual redundancy in a video signal. Finally, coding redundancy can be f urther removed with knowledge of the location of face regions. This coding redundancy reduction is achieved by adopting a 3D run-length-coding method to encode the indexes of the codewords in CVQ. Our bit-rate requirement is 11.41% less than that of the H.261 standard. Furthermore, the quality of ou r decoded images is about 2 dbs better than the. image quality decoded by u sing the H.261 standard. By sacrificing only very little image quality. our proposed coding method can achieve the bit-rate requirement in very low bi t-rate video coding, (C) 2001 Academic Press.