关于非线性量化技术： 我们有“QIM”（量化指数调制）。 该技术使用步长（量化因子）delta的一些量化器以量化原始信号的样本。 在我关于量化步长的研究之后我注意到，这最后可能是小的还是大的。
--Increasing the quantization step size to be coarse decreases the amount of encoded data, and also degrades the quality of the reconstructed picture. For images having a lot of information, degradation in quality is a serious problem.
--Decreasing the quantization step size to be fine increases the amount of encoded data, and also reduces degradation in the quality of the reconstructed picture. For images having little information, degradation in quality is not such a serious problem, and reduction in the amount of encoded data is desirable.
--Thus, it is seen that to select the optimum quantization step size, it is necessary to consider picture quality as well as buffer occupancy.
之后，我有两个问题：
1）量化步长的范围值是多少？
2）可以将0.1设置为量化步长值，以获得非常低的失真Δ
致以最诚挚的问候，
李斯特