2000
@article{PoS2000,
vgclass = {refpap},
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},
url = {http://www.cns.nyu.edu/\~{}eero/texture/},
url1 = {http://ftp.cns.nyu.edu/pub/eero/portilla99.pdf},
url2 = {http://ftp.cns.nyu.edu/pub/eero/portilla99.ps.gz},
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.},
}