Paper Info
Title
The Algorithm and Structure for Digital Normalized Cross-Correlation by Using First-Order Moment.
Abstract
Normalized cross-correlation is an important mathematical tool in digital signal processing. This paper presents a new algorithm and its systolic structure for digital normalized cross-correlation, based on the statistical characteristic of inner-product. We first introduce a relationship between the inner-product in cross-correlation and a first-order moment. Then digital normalized cross-correlation is transformed into a new calculation formula that mainly includes a first-order moment. Finally, by using a fast algorithm for first-order moment, we can compute the first-order moment in this new formula rapidly, and thus develop a fast algorithm for normalized cross-correlation, which contributes to that arbitrary-length digital normalized cross-correlation being performed by a simple procedure and less multiplications. Furthermore, as the algorithm for the first-order moment can be implemented by systolic structure, we design a systolic array for normalized cross-correlation with a seldom multiplier, in order for its fast hardware implementation. The proposed algorithm and systolic array are also improved for reducing their addition complexity. The comparisons with some algorithms and structures have shown the performance of the proposed method.
Year
DOI
Venue
2020
10.3390/s20051353
SENSORS
Keywords
DocType
Volume
normalized cross-correlation,fast algorithm,first-order moment,systolic array,multiplication complexity
Journal
20
Issue
ISSN
Citations 
5.0
1424-8220
0
PageRank 
References 
Authors
0.34
0
4
Name
Order
Citations
PageRank
Chao Pan100.68
Zhicheng Lv200.34
Hua Xia365.24
Hongyan Li410.69