Comparison of Data With Multiple Degrees of Freedom Utilizing the Feature Selective Validation Method
Gang Zhang, Alistair Duffy, Antonio Orlandi, Danilo Di Febo, Lixin Wang, Hugh G. Sasse · IEEE Transactions on Electromagnetic Compatibility · 2016
The feature selective validation method has been shown to provide results that are in broad agreement with the visual assessment of a group of engineers for line, 1-D, data. An implementation using 2-D Fourier transforms and derivatives have been available for some years, but verification of the performance has been difficult to obtain. Further, that approach does not naturally scale well for 3-D and higher degrees of freedom, particularly if there are sizable differences in the number of points in the different directions. This paper describes an approach based on repeated 1-D FSV analyses that overcomes those challenges. The ability of the 2-D case to mirror user perceptions is demonstrated using the LIVE database. Its extension to n-dimensions is also described and includes a suggestion for weighting the algorithm based on the number of data points in a given “direction.”