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Marker-Based Approach for the Automated Selection of a Single Segmentation from a Hierarchical Set of Image Segmentations

机译：基于标记的方法从一组图像分割中自动选择单个分割

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The Hierarchical SEGmentation (HSEG) algorithm, which combines region object finding with region object clustering, has given good performances for multi- and hyperspectral image analysis. This technique produces at its output a hierarchical set of image segmentations. The automated selection of a single segmentation level is often necessary. We propose and investigate the use of automatically selected markers for this purpose. In this paper, a novel Marker-based HSEG (M-HSEG) method for spectral-spatial classification of hyperspectral images is proposed. Two classification-based approaches for automatic marker selection are adapted and compared for this purpose. Then, a novel constrained marker-based HSEG algorithm is applied, resulting in a spectral-spatial classification map. Three different implementations of the M-HSEG method are proposed and their performances in terms of classification accuracies are compared. The experimental results, presented for three hyperspectral airborne images, demonstrate that the proposed approach yields accurate segmentation and classification maps, and thus is attractive for remote sensing image analysis.

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Tarabalka, Y.; Tilton, J. C.; Benediktsson, J. A.; Chanussot, J.;
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年度 2012
页码 1-12
总页数 12
原文格式 PDF
正文语种 eng
中图分类工业技术;
关键词
Imaging techniques ; Image classification ; Image analysis ; Markers ; Remote sensing ; Segments ; Spectrum analysis ; Classifications ; Algorithms;

机译：成像技术;图像分类;图像分析;标记;遥感;分段;频谱分析;分类;算法;

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1. A Marker-Based Approach for the Automated Selection of a Single Segmentation From a Hierarchical Set of Image Segmentations [J] . Tarabalka Y., Tilton J. C., Benediktsson J. A., Selected Topics in Applied Earth Observations and Remote Sensing, IEEE Journal of . 2012,第1期

机译：一种基于标记的方法，可从图像分割的分层集合中自动选择单个分割
2. A fully automated and reproducible level-set segmentation approach for generation of MR-based attenuation correction map of PET images in the brain employing single STE-MR imaging modality [J] . Anahita Fathi Kazerooni, Mohammad Hadi Aarabi, Mohammadreza Ay, EJNMMI Physics . 2014,第S1期

机译：全自动和可再现的水平集分割方法，用于使用单个STE-MR成像方式在大脑中生成基于MR的PET图像的衰减校正图
3. Single STE-MR Acquisition in MR-Based Attenuation Correction of Brain PET Imaging Employing a Fully Automated and Reproducible Level-Set Segmentation Approach [J] . Kazerooni Anahita Fathi, Ay Mohammad Reza, Arfaie Saman, Molecular imaging and biology: MIB : the official publication of the Academy of Molecular Imaging . 2017,第1期

机译：基于MR的衰减校正脑宠物成像的单一STE-MR采集，采用全自动和可重复的水平设定分割方法的脑宠物成像
4. Marker-based Hierarchical Segmentation and classification approach for hyperspectral imagery [C] . Tarabalka Yuliya, Tilton James C., Benediktsson Jon Atli, 2011 IEEE International Conference on Acoustics, Speech and Signal Processing . 2011

机译：基于标记的高光谱图像分层分割和分类方法
5. An automated system for quantitative hierarchical image analysis of malignant gliomas: Developing robust techniques for integrated segmentation/classification and prognosis of glioblastoma multiforme. [D] . Dube, Shishir. 2009

机译：一种用于恶性神经胶质瘤定量层次图像分析的自动化系统：开发强大的技术，用于对多种胶质母细胞瘤进行整合的细分/分类和预后。
6. A fully automated and reproducible level-set segmentation approach for generation of MR-based attenuation correction map of PET images in the brain employing single STE-MR imaging modality [O] . Anahita Fathi Kazerooni, Mohammad Hadi Aarabi, Mohammadreza Ay, 2014

机译：全自动和可再现的水平集分割方法用于使用单个STE-MR成像方式在大脑中生成基于MR的PET图像的衰减校正图
7. A Marker-Based Approach for the Automated Selection of a Single Segmentation from a Hierarchical Set of Image Segmentations [O] . Tilton, J. C., Benediktsson, J. A., Tarabalka, Y., 2012

机译：一种基于标记的方法，可从图像分割的分层集中自动选择单个分割

Marker-Based Approach for the Automated Selection of a Single Segmentation from a Hierarchical Set of Image Segmentations

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