Two Compound Random Field Texture Models
نویسندگان
چکیده
Two novel models for texture representation using parametric compound random field models are introduced. These models consist of a set of several sub-models each having different characteristics along with an underlying structure model which controls transitions between them. The structure model is a two-dimensional probabilistic mixture model either of the Bernoulli or Gaussian mixture type. Local textures are modeled using the fully multispectral three-dimensional causal autoregressive models. Both presented compound random field models allow to reproduce, compress, edit, and enlarge a given measured color, multispectral, or bidirectional texture function (BTF) texture so that ideally both measured and synthetic textures are visually indiscernible.
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