针对纹理合成中基本的MRF类模型在大尺度结构表达上的缺陷,提出了在纹理模式空间和素材空间内对纹元及其分布的新的描述框架:使用纹元基本形和特征向量表示纹元,使用特征纹理表示纹元分布状况.在此结构上进行素材合成,可以保留MRF类模型在素材合成上的优势.实验结果表明,对于结构性较强的纹理,文中方法可以得到更加接近纹理机制的合成结果和某些纹理合成特效.
Markov random field (MRF) as a basic model for texture synthesis is not good at expressing large-size structures and unstable structures due to its inherent insufficiency on long-range relevancy. In this regard, a novel two-phase framework constructed in pattern space and material space is proposed in this paper to describe the texture structures. By the framework, the basic shape and feature vectors are used to decompose textons' shape, while the feature textures are employed to encode the distribution of textons. The framework takes the advantage both of the flexibility and the accuracy from MRF-like methods. Experiments show that for highly structured textures, our method can generate better results, and also produce certain special effects in synthesis.