论文标题
使用全球外观建模的光谱图像分割
Spectral Image Segmentation with Global Appearance Modeling
论文作者
论文摘要
我们引入了一种用于图像分割的新光谱方法，该方法结合了用于全局外观建模的远距离关系。该方法结合了两个不同的图，一个是一个稀疏的图形，它捕获附近像素之间的空间关系，而另一个是一个密集的图，它捕获了所有像素对之间的成对相似性。我们通过结合与每个图相关的马尔可夫链的过渡矩阵，将归一化切割的光谱方法扩展到了这种设置。我们还得出了一种有效的方法来稀疏外观关系的密集图。这导致了一种用于分割高分辨率图像的实用算法。所得的方法可以分割有挑战的图像，而无需进行任何过滤或预处理。
We introduce a new spectral method for image segmentation that incorporates long range relationships for global appearance modeling. The approach combines two different graphs, one is a sparse graph that captures spatial relationships between nearby pixels and another is a dense graph that captures pairwise similarity between all pairs of pixels. We extend the spectral method for Normalized Cuts to this setting by combining the transition matrices of Markov chains associated with each graph. We also derive an efficient method for sparsifying the dense graph of appearance relationships. This leads to a practical algorithm for segmenting high-resolution images. The resulting method can segment challenging images without any filtering or pre-processing.
