A Parametric Texture Model based on Joint Statistics of Complex Wavelet Coefficients

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A Parametric Texture Model based on Joint Statistics of Complex Wavelet Coefficients (2000)

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by Javier Portilla , Eero P. Simoncelli

Venue:	INTERNATIONAL JOURNAL OF COMPUTER VISION
Citations:	423 - 13 self

BibTeX

@ARTICLE{Portilla00aparametric,
    author = {Javier Portilla and Eero P. Simoncelli},
    title = {A Parametric Texture Model based on Joint Statistics of Complex Wavelet Coefficients},
    journal = {INTERNATIONAL JOURNAL OF COMPUTER VISION},
    year = {2000},
    volume = {40},
    number = {1},
    pages = {49--71}
}

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Abstract

We present a universal statistical model for texture images in the context of an overcomplete complex wavelet transform. The model is parameterized by a set of statistics computed on pairs of coefficients corresponding to basis functions at adjacent spatial locations, orientations, and scales. We develop an efficient algorithm for synthesizing random images subject to these constraints, by iteratively projecting onto the set of images satisfying each constraint, and we use this to test the perceptual validity of the model. In particular, we demonstrate the necessity of subgroups of the parameter set by showing examples of texture synthesis that fail when those parameters are removed from the set. We also demonstrate the power of our model by successfully synthesizing examples drawn from a diverse collection of artificial and natural textures.

Keyphrases

complex wavelet coefficient parametric texture model joint statistic diverse collection random image universal statistical model efficient algorithm texture image natural texture texture synthesis overcomplete complex wavelet transform basis function perceptual validity adjacent spatial location

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