Eom K B
Department of Electrical and Computer Engineering, George Washington University, Washington, DC 20052, USA.
J Opt Soc Am A Opt Image Sci Vis. 2001 Aug;18(8):1822-31. doi: 10.1364/josaa.18.001822.
A new class of random field models, called generalized circular autoregressive (GCAR) models, is introduced. GCAR models have noncausal neighbors that have the same autoregressive parameter values if they are on the same circle or ellipse and that have circular or elliptical correlation structures. This model is better for modeling isotropic or anisotropic natural textures than earlier approaches to modeling of isotropic textures and can represent complex textures with a small number of parameters. Parameter estimation is also considered, and a multistep estimation algorithm is presented. Properties of estimators of GCAR models are also investigated. The efficacy of GCAR models in modeling real textures is demonstrated by synthesizing images resembling real textures by use of parameters estimated from textures selected from the Brodatz texture album. Limitations of GCAR models are also discussed.
引入了一类新的随机场模型，称为广义循环自回归（GCAR）模型。GCAR模型具有非因果邻域，如果它们位于同一圆或椭圆上，则具有相同的自回归参数值，并且具有圆形或椭圆形相关结构。与早期的各向同性纹理建模方法相比，该模型更适合对各向同性或各向异性自然纹理进行建模，并且可以用少量参数表示复杂纹理。还考虑了参数估计，并提出了一种多步估计算法。还研究了GCAR模型估计器的性质。通过使用从Brodatz纹理相册中选择的纹理估计的参数合成类似真实纹理的图像，证明了GCAR模型在对真实纹理建模中的有效性。还讨论了GCAR模型的局限性。
