Further Improvement on Dynamic Programming for Optimal Bit Allocation

Dynamic programming algorithms based on Lagrange multiplier method is often used for obtaining an optimal bit allocation strategy to minimize the total distortion given a constrained rate budget in both source and channel coding applictions.Due to possible large quantizer set and improper initialization,the algorithm often suffers from heavy computational complexity.There have been may solutions in recent years to the above question.In this paper,a simple but efficient algorithm is presented to further speed up the convergence of the algorithm.This algorithm can be easily realized and get the final solution much faster.The experimental result shows that our new algorithm can figure out the optimal solution with a speed 5-7 times faster than the original algorithm.

Further improvement on dynamic programming for optimal bit allocation

Dynamic programming algorithms based on Lagrange multiplier method is often used for obtaining an optimal bit allocation strategy to minimize the total distortion given a constrained rate budget in both source and channel coding applications. Due to possible large quantizer set and improper initialization, the algorithm often suffers from heavy computational complexity. There have been many solutions in recent years to the above question. In this paper, a simple but efficient algorithm is presented to further speed up the convergence of the algorithm. This algorithm can be easily realized and get the final solution much faster. The experimental result shows that our new algorithm can figure out the optimal solution with a speed 5-7 times faster than the original algorithm.