The USC Andrew and Erna Viterbi School of Engineering USC Signal and Image Processing Institute USC Ming Hsieh Department of Electrical and Computer Engineering University of Southern California

Technical Report USC-SIPI-264

“Texture Roughness Analysis and Synthesis via Extended Self-Similar (ESS) Model”

by Lance M. Kaplan and C.-C. Jay Kuo

August 1994

The 2-D fractional Brownian motion (fBm) model provides a useful tool to model textured surfaces whose roughness is scale-invariant. To represent textures whose roughness is scale-dependent, we generalize the fBm model to the extended self-similar (ESS) model in this research. We present an estimation algorithm to extract the model parameters from real texture data. Furthermore, a new incremental Fourier synthesis algorithm is proposed to generate the 2-D realizations of the ESS model. Finally, the estimation and rendering methods are combined to synthesize real textured surfaces.

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