Universal Refinable Trellis Coded Quantization

Abstract

We introduce a novel universal refinable trellis quantization scheme (URTCQ) that is suitable for bitplane coding with many reconstruction stages. Existing refinable trellis quantizers either require excessive codebook training and are outperformed by scalar quantization for more than two stages (MS-TCQ, E-TCQ), require a huge computational burden (SR-TCQ) or achieve a good rate distortion performance in the last stage only (UTCQ). The presented quantization technique is a mixture of a scalar quantizer and an improved version of the E-TCQ. For all supported sources only one time training to an i.i.d. uniform source is required and its incremental bitrate is not more than 1 bps for each stage. The complexity is proportional to the number of stages and the number of trellis states. We compare the rate distortion performance of our work on generalized Gaussian i.i.d. sources with the quantizers deployed in JPEG2000 (USDZQ, UTCQ). It turns out that it is in no stage worse than the scalar quantizer and usually outperforms the UTCQ except for the last stage.