Texture representation and synthesis using correlation of complex wavelet coefficient magnitudes

J Portilla and E P Simoncelli

Consejo Superior de Investigaciones Cientificas (CSIC), Madrid, Technical Report 54, Mar 1999.

This paper has been superseded by:
Texture modeling and synthesis using joint statistics of complex wavelet coefficients
J Portilla and E P Simoncelli.
IEEE Workshop on Statistical and Computational Theories of Vision, Jun 1999.

  • Reprint (ps)
    • 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 auto-correlation 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. We also show the flexibility of the representation, by applying to a variety of tasks which can be viewed as constrained image synthesis problems.
  • Listing of all publications