IEEE Trans Pattern Anal Mach Intell. 2016 Jun;38(6):1126-40. doi: 10.1109/TPAMI.2015.2441070. Epub 2015 Sep 22.
Connected filters are well-known for their good contour preservation property. A popular implementation strategy relies on tree-based image representations: for example, one can compute an attribute characterizing the connected component represented by each node of the tree and keep only the nodes for which the attribute is sufficiently high. This operation can be seen as a thresholding of the tree, seen as a graph whose nodes are weighted by the attribute. Rather than being satisfied with a mere thresholding, we propose to expand on this idea, and to apply connected filters on this latest graph. Consequently, the filtering is performed not in the space of the image, but in the space of shapes built from the image. Such a processing of shape-space filtering is a generalization of the existing tree-based connected operators. Indeed, the framework includes the classical existing connected operators by attributes. It also allows us to propose a class of novel connected operators from the leveling family, based on non-increasing attributes. Finally, we also propose a new class of connected operators that we call morphological shapings. Some illustrations and quantitative evaluations demonstrate the usefulness and robustness of the proposed shape-space filters.
连通滤波器以其良好的轮廓保持特性而闻名。一种流行的实现策略依赖于基于树的图像表示：例如，可以计算一个属性来描述树中每个节点表示的连通分量，并仅保留属性足够高的节点。此操作可以看作是对树的阈值处理，将其视为一个节点由属性加权的图。我们不是满足于仅仅进行阈值处理，而是提出扩展这个想法，并将连通滤波器应用于这个最新的图上。因此，过滤不是在图像空间中进行，而是在从图像构建的形状空间中进行。这种对形状空间滤波的处理是现有基于树的连通算子的推广。实际上，该框架通过属性包含了经典的现有连通算子。它还允许我们从基于非递减属性的层次化家族中提出一类新的连通算子。最后，我们还提出了一类我们称之为形态塑造的新的连通算子。一些示例和定量评估证明了所提出的形状空间滤波器的有用性和鲁棒性。
