Title :
New relative multifractal dimension measures
Author :
Dansereau, R. ; Kinsner, W.
Author_Institution :
Dept. of Electr. & Comput. Eng., Manitoba Univ., Winnipeg, Man., Canada
Abstract :
This paper introduces a new class of fractal dimension measure which we call relative multifractal measures. The relative multifractal measures developed are formed through a melding of the Renyi dimension spectrum, which is based on the Renyi generalized entropy, and relative entropy as given with the Kullback-Leibler distance. This new class of multifractal measure is then used to find the relative multifractal complexity differences between two signals, an image and its lossy approximation. It is proposed that relative multifractal measures can be used as the basis for a new form of signal and image quality measure based on signal complexity
Keywords :
data compression; entropy codes; fractals; image coding; spectral analysis; Kullback-Leibler distance; Renyi dimension spectrum; Renyi generalized entropy; fractal dimension measures; image quality; lossy image approximation; relative entropy; relative multifractal complexity differences; signal complexity; signal quality; Electric variables measurement; Entropy; Fractals; Image quality; Loss measurement; Performance evaluation; Probability distribution; Statistics;
Conference_Titel :
Acoustics, Speech, and Signal Processing, 2001. Proceedings. (ICASSP '01). 2001 IEEE International Conference on
Conference_Location :
Salt Lake City, UT
Print_ISBN :
0-7803-7041-4
DOI :
10.1109/ICASSP.2001.941276