Memory-efficient scalable line-based image coding

We study the problem of memory-efficient scalable image compression and investigate some tradeoffs in the complexity versus coding efficiency space. The focus is on a low-complexity algorithm centered around the use of sub-bit-planes, scan-causal modeling, and a simplified arithmetic coder. This algorithm approaches the lowest possible memory usage for scalable wavelet-based image compression and demonstrates that the generation of a scalable bit-stream is not incompatible with a low-memory architecture.