For very low bit-rate video coding such as under 64 kbps, it is unreasonable to encode and transmit all the information. Thus, it is very important to choose the "important" information and encode it efficiently. In this paper, we first propose an image separation-composition method to solve this problem. At the encoder, an image is separated into a low-frequency part and two (horizontal and vertical) edge parts, which are considered as "important" information for human visualization. The low-frequency part is encoded by using block DCT and linear quantization. And the edges are selected by their values and encoded by using Chain coding to remain the most of the important parts for human visualization. At the decoder, the image is reconstructed by first generating the high-frequency parts from the horizontal and vertical edge parts, respectively, and then applying the inverse wavelet transform to the low frequency part and high frequency parts. This composition algorithm has less computational complexity than the conventional analytic/synthetic algorithms because it is not based on iterating approach. Moreover, to reduce the temporal redundancy efficiently, we propose a hierarchical motion detection and a motion interpolation /extrapolation algorithm. We detect motion vectors and motion regions between two reconstructed images and then predict the motion vectors of the current image from the previous detected motion vectors and motion regions by using the interpolation/extrapolation both at the encoder and at the decoder. Therefore, it is unnecessary to transmit the motion vectors and motion regions. This algorithm reduces not only the temporal redundancy but also bit-rates for coding side information . Furthermore, because the motion detection is completely syntax independent, any type of motion detection can be used. We show some simulation results of the proposed video coding algorithm with the coding bit-rate down to 24 kbps and 10 kbps.