Classified zerotree wavelet image coding and adaptive packetization for low-bit-rate transport

In this paper, a novel robust image-coding and adaptive-packetization algorithm suitable for very low bit-rate transport is suggested. This algorithm can be applied to any zerotree-based encoder, such as the embedded zerotree wavelet coder of Shapiro and set partitioning in hierarchical trees by Said and Pearlman. A very explicit segmentation and packetization method of an image bitstream, where the lowest frequency subband is separately encoded from the higher frequency subbands for unequal protection over a noisy channel, is proposed. The trees in the higher frequency subbands are split, classified, and assembled for efficient image coding and packetization according to their initial threshold and subband. The use of these classified trees enables one to make robust packets, while giving priority to some packets. In practice, each packet has a different initial threshold and can be decoded independently. In spite of additional overhead bits required for packetization, the algorithm reported is comparable to the original zerotree-based image coders at low bit rates. Additionally, simulation results show that the new method is resilient under severe packet losses.