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A Relative Fractal Dimension Spectrum for a Perceptual Complexity Measure:
Our Price:    $30.00 US
Article #:    ITJ4006
Number of pages:    73-86 pages
Source:    International Journal of Cognitive Informatics and Natural Intelligence, Vol. 2, Issue 1
Author(s):    Kinsner, W.; Dansereau, R.
Affiliation(s):    University of Manitoba, Canada; University of Manitoba, Canada

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Description
This article presents a derivation of a new relative fractal dimension spectrum, DRq, to measure the dissimilarity between two finite probability distributions originating from various signals. This measure is an extension of the Kullback-Leibler (KL) distance and the Rényi fractal dimension spectrum, Dq. Like the KL distance, DRq determines the dissimilarity between two probability distibutions X and Y of the same size, but does it at different scales, while the scalar KL distance is a single-scale measure. Like the Rényi fractal dimension spectrum, the DRq is also a bounded vectorial measure obtained at different scales and for different moment orders, q. However, unlike the Dq, all the elements of the new DRq become zero when X and Y are the same. Experimental results show that this objective measure is consistent with the subjective mean-opinion-score (MOS) when evaluating the perceptual quality of images reconstructed after their compression. Thus, it could also be used in other areas of cognitive informatics.

 
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