关于非线性量化技术：我们有“QIM”（量化指数调制）。该技术使用一些步长（量化因子）增量的量化器来量化原始信号的样本。在对量化步长进行研究后，我注意到最后一个可以小或大。
--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.
在那之后，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？
此致，
李斯特