A Graph-Based Classification Method for Hyperspectral Images
文献类型：期刊论文
| 作者 | Bai, Jun ; Xiang, Shiming; Pan, Chunhong
|
| 刊名 | IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
 |
| 出版日期 | 2013-02-01 |
| 卷号 | 51期号:2页码:803-817 |
| 关键词 | Classification graph cut (GC) hyperspectral Markov random field (MRF) support vector machine (SVM) |
| 英文摘要 | The goal of this paper is to apply graph cut (GC) theory to the classification of hyperspectral remote sensing images. The task is formulated as a labeling problem on Markov random field (MRF) constructed on the image grid, and GC algorithm is employed to solve this task. In general, a large number of user interactive strikes are necessary to obtain satisfactory segmentation results. Due to the spatial variability of spectral signatures, however, hyperspectral remote sensing images often contain many tiny regions. Labeling all these tiny regions usually needs expensive human labor. To overcome this difficulty, a pixelwise fuzzy classification based on support vector machine (SVM) is first applied. As a result, only pixels with high probabilities are preserved as labeled ones. This generates a pseudouser strike map. This map is then employed for GC to evaluate the truthful likelihoods of class labels and propagate them to the MRF. To evaluate the robustness of our method, we have tested our method on both large and small training sets. Additionally, comparisons are made between the results of SVM, SVM with stacking neighboring vectors, SVM with morphological preprocessing, extraction and classification of homogeneous objects, and our method. Comparative experimental results demonstrate the validity of our method. |
| WOS标题词 | Science & Technology ; Physical Sciences ; Technology |
| 类目[WOS] | Geochemistry & Geophysics ; Engineering, Electrical & Electronic ; Remote Sensing ; Imaging Science & Photographic Technology |
| 研究领域[WOS] | Geochemistry & Geophysics ; Engineering ; Remote Sensing ; Imaging Science & Photographic Technology |
| 关键词[WOS] | SUPPORT VECTOR MACHINES ; MORPHOLOGICAL PROFILES ; URBAN AREAS ; SPATIAL CLASSIFICATION ; CUTS ; SEGMENTATION ; EXTRACTION ; KERNELS ; FIELDS ; MODEL |
| 收录类别 | SCI |
| 语种 | 英语 |
| WOS记录号 | WOS:000314019500008 |
| 源URL | [http://ir.ia.ac.cn/handle/173211/3708]  |
| 专题 | 自动化研究所_模式识别国家重点实验室_遥感图像处理团队 |
| 作者单位 | Chinese Acad Sci, Natl Lab Pattern Recognit, Inst Automat, Beijing 100190, Peoples R China |
| 推荐引用方式 GB/T 7714 | Bai, Jun,Xiang, Shiming,Pan, Chunhong. A Graph-Based Classification Method for Hyperspectral Images[J]. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING,2013,51(2):803-817. |
| APA | Bai, Jun,Xiang, Shiming,&Pan, Chunhong.(2013).A Graph-Based Classification Method for Hyperspectral Images.IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING,51(2),803-817. |
| MLA | Bai, Jun,et al."A Graph-Based Classification Method for Hyperspectral Images".IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING 51.2(2013):803-817. |
入库方式： OAI收割
来源：自动化研究所
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