PROJECT TITLE :
Comparison of Data With Multiple Degrees of Freedom Utilizing the Feature Selective Validation Method
The feature selective validation methodology has been shown to produce results that are in broad agreement with the visual assessment of a cluster of engineers for line, one-D, information. An implementation using 2-D Fourier transforms and derivatives are obtainable for a few years, but verification of the performance has been difficult to obtain. More, that approach does not naturally scale well for three-D and higher degrees of freedom, significantly if there are sizable variations in the quantity of points in the various directions. This paper describes an approach primarily based on repeated 1-D FSV analyses that overcomes those challenges. The flexibility of the two-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 quantity of knowledge points during a given “direction.”
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