摘要
为了更好地解决海量录波数据存储空间过大,数据传输效率低的问题,提出将二维提升小波、游程编码、哈夫曼编码相结合的数据压缩方法.首先将实时检测的一维电能质量数据按照周期截取,并依次排列形成二维的数据,对该数据进行二维提升小波分解得到低频系数和高频系数,然后对高频系数进行阈值量化,最后将量化后的数据与低频系数用零行程和哈夫曼进行编码,以进一步提高数据的压缩比.仿真实验结果表明,本文算法相比较传统的二维离散小波算法,能在压缩比提高一倍左右时将误差限制在很小的范围内.
In order to resolve well the problems of excessive storage space for massive recorded data and low efficiency of data transmission, a data compression method is proposed, where 2-D lifting wavelet, run length coding, and Huffman coding are combined. First, the real-time detected 1-D power quality data is intercepted periodically and arranged sequentially into as 2-D data, and 2-D lifting of wavelet decomposi- tion of this data is conducted to get low- and high- frequency coefficients. Then, the high-frequency coeffi- cient is threshold quantized. Finally, the quantized data and low-frequency coefficient are coded by means of zero run length coding and Huffman coding to improve further the data compression ratio. It is shown by simulation result that, compared to traditional 2-D discrete wavelet algorithm, the algorithm presented in this paper can be used to confine the error to a very small region when the compression ratio is increased by about twice.
出处
《兰州理工大学学报》
CAS
北大核心
2016年第6期94-98,共5页
Journal of Lanzhou University of Technology
基金
国家自然科学基金(51267011)
关键词
电能质量
数据压缩
二维提升整数小波
游程编码
哈夫曼编码
power quality
data compression
2-D lifting of integer wavelet
run length coding
Huffman coding
