A deletion cost based compression algorithm for linear vector data

摘要

A new deletion-cost based compression algorithm (DCA) for linear vector data is proposed. To each curve-the basic element of linear vector data, all the deletion costs of its middle nodes are calculated, and the minimum deletion cost is compared with the pre-defined threshold. If the former is greater than or equal to the latter, all remaining nodes are reserved and the curve's compression process is finished. Otherwise, the node with the minimal deletion cost is deleted, its two neighbors' deletion costs are updated, and the same loop of the compressed curve repeats till the termination. Experiment results show that DCA outperforms Douglas-Peucker algorithm (DPA) in compression accuracy and execution efficiency as well.