Clustering algorithm based on wavelet transform is efficient, and which can detect clusters of arbitrary shape. It is insensitive to the outliers and the order of input data. However, efficiency of the algorithm would be degraded, and computation complexity of the algorithm would be considerable with increase of clustering dimensions. A bottom-u Pmethod is put forward to make the original algorithm fit to clustering in high dimension, and the scalability of the improved algorithm is enhanced by parallelization. The experiment demonstrates that the improved algorithm has no impact on quality of clustering and has a good efficient in high dimension clustering and in decrease of comnutation comnlexity.
