Low-complexity waveform coding via alphabet and sample-set partitioning
Amir Said, William A. Pearlman · 2002
We propose a new low-complexity entropy-coding method to be used for coding waveform signals. It is based on the combination of two schemes: (1) an alphabet partitioning method to reduce the complexity of the entropy-coding process; (2) a new recursive set partitioning entropy-coding process that achieves rates smaller than first order entropy even with fast Huffman adaptive codecs. Numerical results with its application for lossy and loss-less image compression show the efficacy of the new method, comparable to the best known methods.