A Simple Fast Codebook Training Algorithm by Entropy Sequence for Vector Quantization

摘要

The traditional training algorithm for vector quantization such as the LBG algorithm uses the convergence of distortion sequence as the condition of the end of algorithm. We presented a novel training algorithm for vector quantization in this paper. The convergence of the entropy sequence of each region sequence is employed as the condition of the end of the algorithm. Compared with the famous LBG algorithm, it is simple, fast and easy to be comprehended and controlled. We test the performance of the algorithm by typical test image Lena and Barb. The result shows that the PSNR difference between the algorithm and LBG is less than 0.ldB, but the running time of it is at most one second of LBG