| 摘要 |
A transform-based image compression framework called local zerotree (LZT) coding partitions the transform coefficients into small groups, each of which is encoded independently using popular zerotree algorithms. The LZT coder achieves similar coding performances as current state-of-the-art embedded coders. The advantage of this coding method is fourfold: (i) because of the reduction of memory buffering, LZT reduces the complexity of the codec implementation and increases the speed of tHE zerotree algorithm significantly, especially in hardware; (ii) LZT processes large images under limited memory constraint; (iii) LZT supports parallel processing mode as long as the transform in use has that capability; and (iv) LZT facilitates the coding/decoding of regions of interest. The penalty in coding performance is minute compared to global zerotree predecessors in that there are only a few extra bytes of side information. This new coder provides numerous other advantages: faster and simpler hardware implementation, supporting parallel processing mode, facilitating region-of-interest coding/decoding, and capable of processing large images under limited memory constraint. The only properties that LZT sacrifices are full embededness and progressive transmission. |
