灰度标记的ift分水岭

R. Lotufo, A. Falcão, F. Zampirolli
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引用次数: 74

摘要

分水岭变换和形态重构是数学形态学框架下图像分割的两个重要算子。在许多情况下,分割需要对重建图像进行经典的分水岭变换。在本文中,我们介绍了一种从灰度标记- ift分水岭同时计算重建图像和经典分水岭变换的方法,无需显式计算任何区域最小值。该方法基于图像森林变换(IFT)——一种将图像处理问题简化为图中最小代价路径森林问题的统一而有效的方法。作为额外的贡献,我们证明了(i)标记的ift流域成本图与高级灰度重建的输出相同;(ii)其他重构算法不属于流域;(3)与当前经典流域方法相比,本文提出的方法具有竞争优势。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
IFT-Watershed from gray-scale marker
The watershed transform and the morphological reconstruction are two of the most important operators for image segmentation in the framework of mathematical morphology. In many situations, the segmentation requires the classical watershed transform of a reconstructed image. In this paper, we introduce the IFT-watershed from gray scale marker-a method to compute at same time, the reconstruction and the classical watershed transform of the reconstructed image, without explicit computation of any regional minima. The method is based on the Image Foresting Transform (IFT)-a unified and efficient approach to reduce image processing problems to a minimum-cost path forest problem in a graph. As additional contributions, we demonstrate that (i) the cost map of the IFT-watershed from markers is identical to the output of the superior gray scale reconstruction; (ii) other reconstruction algorithms are not watersheds; and (iii) the proposed method achieves competitive advantages as compared to the current classical watershed approach.
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