TEXTURE ROUGHNESS ANALYSIS AND SYNTHESIS VIA EXTENDED SELF-SIMILAR (ESS) MODEL

被引:59
|
作者
KAPLAN, LM
KUO, CCJ
机构
[1] UNIV SO CALIF, INST SIGNAL & IMAGE PROC, LOS ANGELES, CA 90089 USA
[2] UNIV SO CALIF, DEPT ELECT ENGN SYST, LOS ANGELES, CA 90089 USA
关键词
FRACTALS; FRACTIONAL BROWNIAN MOTION; PROCESSES WITH STATIONARY INCREMENTS; TERRAIN MODELING; TEXTURE ANALYSIS; TEXTURE SYNTHESIS; RANDOM FIELDS; ROUGHNESS PERCEPTION;
D O I
10.1109/34.473230
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The 2D 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 selfsimilar (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 2D realizations of the ESS model. Finally, the estimation and rendering methods are combined to synthesize real textured surfaces.
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页码:1043 / 1056
页数:14
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