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Basic and Fine Structure of Pairwise Interactions in Gibbs Texture Models

机译:Gibbs纹理模型中成对相互作用的基本和精细结构

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摘要

Gibbs models with multiple pairwise pixel interactions permit us to estimate characteristic interaction structures of spatially homogeneous image textures. Interactions with partial energies over a particular threshold form a basic structure that is sufficient to model a specific group of stochastic textures. Another group, referred here to as regular textures, permits us to reduce the basic structure in size, providing only a few primary interactions are responsible for this structure. If the primary interactions can be considered as statistically independent, a sequential learning scheme reduces the basic structure and complements it with a fine structure describing characteristic minor details of a texture. Whereas the regular textures are described more precisely by the basic and fine interaction structures, the sequential search may deteriorate the basic interaction structure of the stochastic textures.
机译:具有多个成对像素相互作用的吉布斯模型使我们能够估计空间均匀图像纹理的特征相互作用结构。与超过特定阈值的部分能量的相互作用形成基本模型,该模型足以对特定的一组随机纹理进行建模。另一组,在这里称为常规纹理,允许我们减小基本结构的大小,但前提是只有少数主要交互对此结构负责。如果可以将主要交互视为统计上独立的,则顺序学习方案会减少基本结构,并用描述纹理特征性次要细节的精细结构对其进行补充。尽管基本纹理和精细交互结构更精确地描述了常规纹理,但是顺序搜索可能会使随机纹理的基本交互结构恶化。

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