摘要
针对数学领域内的自相关函数概念的物理意义不明确、通用性不强等缺点,从信息论与编码的角度出发,提出了一种基于游程序列的二元数据相关性的评价方法。首先将黑白二值图像通过扫描形成一维的二元游程序列,然后分成白游程和黑游程两种情况分别进行参数统计,通过相应的算法得到归一化的自相关性指标。理论分析与实验仿真结果表明,该指标物理意义明确,能进行二元数据相关性的纵向比较,在不进行编码的情况下,与编码的效果一致,从而验证了该算法的可行性与有效性。
In order to overcome the indefinite physical meaning and low versatility of autocorrelation function,a binary data correlation based on run-length is presented according to information theory.Binary image is scanned to form the run-length.White and black run-lengths are counted respectively,and normalized correlation is obtained by the method.Theory research and simulation show that the metrics has definite physical meaning and can be compared with others.It has the consistent results with encoding,which validates its rationality and validity.
作者
宫娜娜
Gong Nana(School of Information Engineering, Huanghe S＆T College,Zhengzhou 450063, Chin)
出处
《电子测量技术》
2016年第12期180-183,188,共5页
Electronic Measurement Technology
基金
河南省教育厅项目(15A510031)
郑州市科技攻关计划项目(20120411)
郑州市物联网传感技术及其应用重点实验室(114PYFZX504)资助项目
关键词
相关性
游程长度
哈夫曼编码
压缩比
correlation
run-length
huffman encoding
compression ratio
