PMID: 15376952Sep 21, 2004Paper

Texture decomposition by harmonics extraction from higher order statistics

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
Yong Huang, Kap Luk Chan

Abstract

In this paper, a method of harmonics extraction from Higher Order Statistics (HOS) is developed for texture decomposition. We show that the diagonal slice of the fourth-order cumulants is proportional to the autocorrelation of a related noiseless sinusoidal signal with identical frequencies. We propose to use this fourth-order cumulants slice to estimate a power spectrum from which the harmonic frequencies can be easily extracted. Hence, a texture can be decomposed into deterministic components and indeterministic components as in a unified texture model through a Wold-like decomposition procedure. The simulation and experimental results demonstrated that this method is effective for texture decomposition and it performs better than traditional lower order statistics based decomposition methods.

References

Jan 1, 1995·IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society·T E Hall, G B Giannakis
Jan 1, 1995·IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society·J M FrancosJ W Woods
Jan 1, 1983·IEEE Transactions on Pattern Analysis and Machine Intelligence·G R Cross, A K Jain
Jan 1, 1986·IEEE Transactions on Pattern Analysis and Machine Intelligence·F M VilnrotterK E Price

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Citations

Dec 3, 2010·Optics Letters·Ivan Moreno
Nov 18, 2014·Journal of the Optical Society of America. A, Optics, Image Science, and Vision·Ivan MorenoMaximino Avendaño-Alejo

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