拓扑图格独立分量分析和谱聚类支持的纹理探测

提出的纹理探测方法首先采用拓扑图格独立分量分析(TICA)分别对每个观测纹理进行学习，获得分离基．分离基的作用相当于滤波器，并通过最大响应准则得到选择．从不同纹理选择的滤波器构成一个滤波器集；为了计算探测点的纹理特征，测试图像被分解为滤波器通道。最后，探测点被视为谱图的顶点，根据谱聚类(SC)对谱图的切分结果，递归地分离出探测点．实验结果表明，这一方法行之有效。

Texture Probing Via Topographic Independent Component Analysis and Spectral Cluster

The goal of texture probing is to find the locations of the observed textures in an image by probing points. For an observed texture image, the topographic independent component analysis (TICA) is employed first to learn the un-mixing bases. The bases, acting as filters, are selected further by the criterion of the maximum response. All the selected filters from the observed texture images are collected together to construct a filter bank. Then, the mosaic texture image to be tested is decomposed into filter channels to calculate the texture features of the probing points. To group these probing points, a spectral graph is constructed by treating them as its vertices. In light of the cut on the spectral graph by a spectral cluster (SC), probing point sets are finally separated recursively. Experiments on mosaic texture images show that the proposed method gives satisfactory results.