High quality video transport is a key to the successful offering of networked multimedia or entertainment video services, especially under stringent bandwidth limitations. Video coding techniques that improve visual quality are thus of much interest. This paper reports a video coding scheme designed to transmit high quality HDTV at about 15 Mbps, a CCIR standard video at about 4 Mbps, or the common intermediate format (CIF) video at about 1 Mbps. To improve the known art of video compression, two techniques were further explored. One reduces the temporal redundancy of the input information, essentially by using a switched motion compensation technique. The other takes further advantage of spatial correlations in lossless spatial coding, essentially by using high order entropy coding of the quantized symbols. Two representative motion compensation techniques, the conventional frame-based motion compensation and a new field-adjusted motion compensation (FAMC) currently being proposed at the MPEG2 committee, were analyzed and compared with the proposed switched motion compensation. Based on the mean square prediction error of four test sequences, the new scheme achieves a consistent gain, at twice the processing complexity of the conventional scheme but at only 5% the processing complexity of the FAMC. This forward directional prediction is especially suitable for low delay coding in interactive visual communications, even though it can also incorporate bi-directional prediction to improve performance. The high-order entropy coding technique explored in this paper gives 27% lower rate than conventional run-length/Huffman coding. The required number of high-order entropy code tables is reduced by 97% by our innovative code table reduction technique. Compared to the results we reported before, the required number of code tables is further reduced by about 40% by merging similar codebooks from different components of the video source. The combined scheme using the block-switched motion compensation and high-order entropy coding reduces the total rate by 25% compared with the compression scheme we tested before, and achieves a comparable very good visual quality.