User:Sirohimanshu/sandbox

 ADVANTAGES OF VECTOR QUANTIZATION OVER SCALAR QUANTIZATION

1: Vector Quantization can lower the average distortion with the number of reconstruction levels held constant.

2: Vector Quantization can reduce the number of reconstruction levels when distortion is held constant.

3: The most significant way Vector Quantization can improve performance over Scalar Quantization is by exploiting the statistical dependence among scalars in the block.

4: Vector Quantization is also more effective than Scalar Quantization When the source output values are not correlated.

5: In Scalar Quantization, in One Dimension, the quantization regions are restricted to be in intervals(i.e., Output points are restricted to be rectangular grids) and the only parameter we can manipulate is the size of the interval. While, in Vector Quantization, When we divide the input into vectors of some length n, the quantization regions are no longer restricted to be rectangles or squares, we have the freedom to divide the range of the inputs in an infinite number of ways.

6: In Scalar Quantization, the Granular Error is affected by size of quantization interval only, while in Vector Quantization, Granular Error is affected by the both shape and size of quantization interval.

7: Vector Quantization provides more flexibility towards modifications than Scalar Quantization. The flexibility of Vector Quantization towards modification increases with increasing dimension.

8: Vector Quantization have improved performance when there is sample to sample dependence of input, While not in Scalar Quantization.

9: Vector Quantization have improved performance when there is not the sample to sample dependence of input, While not in Scalar Quantization.