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