Texture Modeling and Synthesis using Joint Statistics of Complex Wavelet Coefficients (1999)
| Venue: | IN IEEE WORKSHOP ON STATISTICAL AND COMPUTATIONAL THEORIES OF VISION, FORT COLLINS |
| Citations: | 22 - 2 self |
BibTeX
@INPROCEEDINGS{Portilla99texturemodeling,
author = {Javier Portilla and Eero P Simoncelli},
title = {Texture Modeling and Synthesis using Joint Statistics of Complex Wavelet Coefficients},
booktitle = {IN IEEE WORKSHOP ON STATISTICAL AND COMPUTATIONAL THEORIES OF VISION, FORT COLLINS},
year = {1999},
publisher = {}
}
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Abstract
We present a statistical characterization of texture images in the context of an overcomplete complex wavelet transform. The characterization is based on empirical observations of statistical regularities in such images, and parameterized by (1) the local autocorrelation of the coefficients in each subband; (2) both the local auto-correlation and cross-correlation of coefficient magnitudes at other orientations and spatial scales; and (3) the first few moments of the image pixel histogram. We develop an efficient algorithm for synthesizing random images subject to these constraints using alternated projections, and demonstrate its effectiveness on a wide range of synthetic and natural textures. In particular, we show that many important structural elements in textures (e.g., edges, repeated patterns or alternated patches of simpler texture), can be captured through joint second order statistics of the coefficient magnitudes. We also show the flexibility of the representation, by applying to a variety...
