Local linear transforms for texture measurements
Local linear transforms for texture measurements
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DOI：
10.1016/0165-1684(86)90095-2
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发表时间：
1986-07
影响因子：
4.4
通讯作者：
M. Unser
中科院分区：
文献类型：
--
作者：
M. Unser
在受限制的邻域中的像素的N阶概率密度函数可以由沿沿着适当选择的轴计算的N个直方图（或一些对应的矩）的集合来表征。这些轴上的投影是从局部邻域向量的局部线性变换获得的。这种方法是密切相关的富尔特银行分析方法，并给出了统计理由的卷积算子或局部匹配的纹理属性的提取。最佳和次优的线性算子，推导出纹理分析和分类。实验结果表明，该方法是鲁棒的，灵活的，它执行以及标准的基于共生的纹理分类方法。所提出的方法，使纹理表征与较低数量的功能，它也是计算上更有吸引力。
TheNth order probability density function for pixels in a restricted neighborhood may be characterized by a set ofNhistograms (or some corresponding moments) computed along appropriately chosen axes. The projections on those axes are obtained from a local linear transform of the local neighborhood vector. This approach is closely related to fulter bank analysis methods and gives a statistical justification for the extraction of texture properties by means of convolution operators or local matches. Optimal and sub-optimal linear operators are derived for texture analysis and classification. Experimental results indicate that the method is robust, flexible, and that it performs as well as standard co-occurrence based methods for texture classification. The proposed approach enables texture characterization with a lower number of features and it is also computationally more appealing.