首页> 外文期刊>IEEE Transactions on Image Processing >Image segmentation and analysis via multiscale gradient watershed hierarchies
【24h】

Image segmentation and analysis via multiscale gradient watershed hierarchies

机译:通过多尺度梯度流域层次结构进行图像分割和分析

获取原文
获取原文并翻译 | 示例
       

摘要

Multiscale image analysis has been used successfully in a number of applications to classify image features according to their relative scales. As a consequence, much has been learned about the scale-space behavior of intensity extrema, edges, intensity ridges, and grey-level blobs. We investigate the multiscale behavior of gradient watershed regions. These regions are defined in terms of the gradient properties of the gradient magnitude of the original image. Boundaries of gradient watershed regions correspond to the edges of objects in an image. Multiscale analysis of intensity minima in the gradient magnitude image provides a mechanism for imposing a scale-based hierarchy on the watersheds associated with these minima. This hierarchy can be used to label watershed boundaries according to their scale. This provides valuable insight into the multiscale properties of edges in an image without following these curves through scale-space. In addition, the gradient watershed region hierarchy can be used for automatic or interactive image segmentation. By selecting subtrees of the region hierarchy, visually sensible objects in an image can be easily constructed.
机译:多尺度图像分析已成功用于许多应用中,以根据其相对比例对图像特征进行分类。结果,关于强度极值,边缘,强度脊和灰度斑点的比例空间行为已学到很多。我们研究了梯度流域区域的多尺度行为。这些区域是根据原始图像的梯度大小的梯度属性定义的。梯度分水岭区域的边界对应于图像中对象的边缘。梯度幅值图像中强度极小值的多尺度分析提供了一种机制,用于在与这些极小值相关的分水岭上施加基于尺度的层次结构。此层次结构可用于根据分水岭的规模标注分水岭边界。这提供了对图像边缘多尺度属性的有价值的见解,而无需遵循这些曲线穿过尺度空间。此外,梯度分水岭区域层次结构可用于自动或交互式图像分割。通过选择区域层次结构的子树,可以轻松构造图像中的视觉敏感对象。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号