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论文:2013,Vol:31,Issue(6):958-961 |
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引用本文： |
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周培诚, 韩军伟, 程塨, 李晖晖, 郭雷. 基于稀疏表达的遥感图像检索[J]. 西北工业大学 |
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Zhou Peicheng, Han Junwei, Cheng Gong, Li Huihui, Guo Lei. Remote Sensing Images Retrieval Based on Sparse Representation[J]. Northwestern polytechnical university |
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| 基于稀疏表达的遥感图像检索 |
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| 周培诚, 韩军伟, 程塨, 李晖晖, 郭雷 |
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| 西北工业大学 自动化学院, 陕西 西安 710072 |
| 摘要: |
| 针对遥感图像如何快速、准确检索的问题,提出了基于稀疏表达理论的遥感图像检索新方法。该方法首先利用在线字典学习算法对查询图像和数据库图像分别训练过完备字典并将训练得到的字典作为图像的特征描述,然后利用基于特征稀疏表达的图像相似性评估算法计算查询图像与数据库图像的相似度,最后根据相似度的降序排列得到检索结果。与现有最新方法的对比实验证明了该方法的有效性。 |
| 关键词:
稀疏表达
字典学习
遥感图像检索
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| Remote Sensing Images Retrieval Based on Sparse Representation |
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| Zhou Peicheng, Han Junwei, Cheng Gong, Li Huihui, Guo Lei |
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| Department of Automatic Control, Northwestern Polytechnical University, Xi'an 710072, China |
| Abstract: |
| To retrieve remote sensing images quickly and accurately, we use the online dictionary learning algorithm to train an over-complete dictionary of query images and database images respectively.The trained dic-tionary is used as an image′s feature description.Then we calculate the similarity between query image and database image with the image similarity evaluation algorithm which is based on the sparse representation of image features. Finally we retrieve the remote sensing images according to the descending order of similarity.The experimental re-sults, given in Figs.4, 5 and 6 and Table 1, and their comparison with the existing methods show preliminarily that our novel remote sensing image retrieval method based on sparse representation can accurately retrieve remote sens -ing images. |
| Key words:
algorithms
image processing
image retrieval
remote sensing
database image
query image
similarity evaluation
sparse representation
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| 收稿日期: 2013-04-16
修回日期:
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| DOI: |
| 基金项目: 国家自然科学基金(61005018、91120005);西北工业大学基础研究基金(NPU-Z2013105)资助 |
| 通讯作者:
Email： |
| 作者简介: 周培诚(1988-),西北工业大学硕士研究生,主要从事遥感图像处理及模式识别的研究。
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| 相关功能 |
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| 作者相关文章 |
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| 周培诚 在本刊中的所有文章 |
| 韩军伟 在本刊中的所有文章 |
| 程塨 在本刊中的所有文章 |
| 李晖晖 在本刊中的所有文章 |
| 郭雷 在本刊中的所有文章 |
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参考文献: |
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