A Relative Fractal Dimension Spectrum as a Complexity Measure
This paper 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 Renyi 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 Renyi 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.
Monofractals and multifractals scalar and vector fractal dimensions Rényi generalized entropy, Rényi relative fractal dimension spectrum
W. Kinsner R. Dansereau
Signal and Data Compression Laboratory Department of Electrical and Computer Engineering University the Institute of Industrial Mathematical Sciences and Telecommunications Research Laboratories, TRLa
国际会议
Firth IEEE International Conference on Cognitive Informatics(第五届认知信息国际会议)
北京
英文
200-208
2006-07-17（万方平台首次上网日期，不代表论文的发表时间）