Particle Swarm Optimization based dictionary learning for remote sensing big data
文献类型：期刊论文
| 作者 | Wang, Lizhe1; Geng, Hao1; Liu, Peng1; Lu, Ke1; Kolodziej, Joanna1; Ranjan, Rajiv1; Zomaya, Albert Y.1 |
| 刊名 | KNOWLEDGE-BASED SYSTEMS
 |
| 出版日期 | 2015 |
| 卷号 | 79页码:243-249 |
| 关键词 | Online dictionary learning Particle Swarm Optimization Sparse representation Big data Machine learning |
| 通讯作者 | Wang, LZ (reprint author), Chinese Acad Sci, Inst Remote Sensing & Digital Earth, Beijing 100864, Peoples R China. |
| 英文摘要 | Dictionary learning, which is based on sparse coding, has been frequently applied to many tasks related to remote sensing processes. Recently, many new non-analytic dictionary-learning algorithms have been proposed. Some are based on online learning. In online learning, data can be sequentially incorporated into the computation process. Therefore, these algorithms can train dictionaries using large-scale remote sensing images. However, their accuracy is decreased for two reasons. On one hand, it is a strategy of updating all atoms at once; on the other, the direction of optimization, such as the gradient, is not well estimated because of the complexity of the data and the model. In this paper, we propose a method of improved online dictionary learning based on Particle Swarm Optimization (PSO). In our iterations, we reasonably selected special atoms within the dictionary and then introduced the PSO into the atom-updating stage of the dictionary-learning model. Furthermore, to guide the direction of the optimization, the prior reference data were introduced into the PSO model. As a result, the movement dimension of the particles is reasonably limited and the accuracy and effectiveness of the dictionary are promoted, but without heavy computational burdens. Experiments confirm that our proposed algorithm improves the performance of the algorithm for large-scale remote sensing images, and our method also has a better effect on noise suppression. (C) 2014 Elsevier B.V. All rights reserved. |
| 研究领域[WOS] | Computer Science, Artificial Intelligence |
| 收录类别 | SCI ; EI |
| 语种 | 英语 |
| WOS记录号 | WOS:000351962500006 |
| 源URL | [http://ir.ceode.ac.cn/handle/183411/38221]  |
| 专题 | 遥感与数字地球研究所_SCI/EI期刊论文_期刊论文 |
| 作者单位 | 1.[Wang, Lizhe 2.Liu, Peng] Chinese Acad Sci, Inst Remote Sensing & Digital Earth, Beijing 100864, Peoples R China 3.[Geng, Hao] Univ Sci & Technol China, Dept Elect Engn & Informat Sci, Beijing, Peoples R China 4.[Lu, Ke] Univ Chinese Acad Sci, Chinese Acad Sci, Beijing, Peoples R China 5.[Kolodziej, Joanna] Cracow Univ Technol, Inst Comp Sci, PL-30084 Krakow, Poland 6.[Ranjan, Rajiv] CSIRO, Melbourne, Vic, Australia 7.[Zomaya, Albert Y.] Univ Sydney, Sch Informat Technol, Sydney, NSW 2006, Australia |
| 推荐引用方式 GB/T 7714 | Wang, Lizhe,Geng, Hao,Liu, Peng,et al. Particle Swarm Optimization based dictionary learning for remote sensing big data[J]. KNOWLEDGE-BASED SYSTEMS,2015,79:243-249. |
| APA | Wang, Lizhe.,Geng, Hao.,Liu, Peng.,Lu, Ke.,Kolodziej, Joanna.,...&Zomaya, Albert Y..(2015).Particle Swarm Optimization based dictionary learning for remote sensing big data.KNOWLEDGE-BASED SYSTEMS,79,243-249. |
| MLA | Wang, Lizhe,et al."Particle Swarm Optimization based dictionary learning for remote sensing big data".KNOWLEDGE-BASED SYSTEMS 79(2015):243-249. |
入库方式： OAI收割
来源：遥感与数字地球研究所
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