Dept. of Electr. Eng., Utah Univ., Salt Lake City, UT.
IEEE Trans Image Process. 1992;1(1):11-7. doi: 10.1109/83.128027.
The author considers vector quantization that uses the L (1) distortion measure for its implementation. A gradient-based approach for codebook design that does not require any multiplications or median computation is proposed. Convergence of this method is proved rigorously under very mild conditions. Simulation examples comparing the performance of this technique with the LBG algorithm show that the gradient-based method, in spite of its simplicity, produces codebooks with average distortions that are comparable to the LBG algorithm. The codebook design algorithm is then extended to a distortion measure that has piecewise-linear characteristics. Once again, by appropriate selection of the parameters of the distortion measure, the encoding as well as the codebook design can be implemented with zero multiplications. The author applies the techniques in predictive vector quantization of images and demonstrates the viability of multiplication-free predictive vector quantization of image data.
作者考虑使用 L(1)失真度量进行矢量量化。提出了一种基于梯度的码本设计方法，该方法不需要任何乘法或中位数计算。在非常温和的条件下，严格证明了该方法的收敛性。与 LBG 算法的性能进行比较的仿真示例表明，尽管该基于梯度的方法很简单，但生成的码本的平均失真与 LBG 算法相当。然后将码本设计算法扩展到具有分段线性特性的失真度量。同样，通过适当选择失真度量的参数，可以实现零乘法的编码以及码本设计。作者将这些技术应用于图像的预测矢量量化中，并证明了图像数据的无乘法预测矢量量化的可行性。
