Dept. of Electr. Eng., Princeton Univ., NJ.
IEEE Trans Image Process. 1997;6(5):677-93. doi: 10.1109/83.568925.
A new class of image coding algorithms coupling standard scalar quantization of frequency coefficients with tree-structured quantization (related to spatial structures) has attracted wide attention because its good performance appears to confirm the promised efficiencies of hierarchical representation. This paper addresses the problem of how spatial quantization modes and standard scalar quantization can be applied in a jointly optimal fashion in an image coder. We consider zerotree quantization (zeroing out tree-structured sets of wavelet coefficients) and the simplest form of scalar quantization (a single common uniform scalar quantizer applied to all nonzeroed coefficients), and we formalize the problem of optimizing their joint application. We develop an image coding algorithm for solving the resulting optimization problem. Despite the basic form of the two quantizers considered, the resulting algorithm demonstrates coding performance that is competitive, often outperforming the very best coding algorithms in the literature.
一种将频率系数的标准标量量化与树结构量化（与空间结构相关）相结合的新型图像编码算法，因其良好的性能似乎证实了分层表示的预期效率而引起了广泛关注。本文探讨了在图像编码器中如何以联合最优的方式应用空间量化模式和标准标量量化的问题。我们考虑零树量化（对小波系数的树状集合进行置零）和最简单形式的标量量化（应用于所有非零系数的单个通用均匀标量量化器），并形式化了优化它们联合应用的问题。我们开发了一种图像编码算法来解决由此产生的优化问题。尽管所考虑的两种量化器形式基本，但所得到的算法展示了具有竞争力的编码性能，通常优于文献中最好的编码算法。
