Knowledge Resource Center for Ecological Environment in Arid Area
DOI | 10.3390/s17061295 |
Remote Sensing Image Change Detection Based on NSCT-HMT Model and Its Application | |
Chen, Pengyun1; Zhang, Yichen1; Jia, Zhenhong1; Yang, Jie2; Kasabov, Nikola3 | |
通讯作者 | Jia, Zhenhong |
来源期刊 | SENSORS |
ISSN | 1424-8220 |
出版年 | 2017 |
卷号 | 17期号:6 |
英文摘要 | Traditional image change detection based on a non-subsampled contourlet transform always ignores the neighborhood information’s relationship to the non-subsampled contourlet coefficients, and the detection results are susceptible to noise interference. To address these disadvantages, we propose a denoising method based on the non-subsampled contourlet transform domain that uses the Hidden Markov Tree model (NSCT-HMT) for change detection of remote sensing images. First, the ENVI software is used to calibrate the original remote sensing images. After that, the mean-ratio operation is adopted to obtain the difference image that will be denoised by the NSCT-HMT model. Then, using the Fuzzy Local Information C-means (FLICM) algorithm, the difference image is divided into the change area and unchanged area. The proposed algorithm is applied to a real remote sensing data set. The application results show that the proposed algorithm can effectively suppress clutter noise, and retain more detailed information from the original images. The proposed algorithm has higher detection accuracy than the Markov Random Field-Fuzzy C-means (MRF-FCM), the non-subsampled contourlet transform-Fuzzy C-means clustering (NSCT-FCM), the pointwise approach and graph theory (PA-GT), and the Principal Component Analysis-Nonlocal Means (PCA-NLM) denosing algorithm. Finally, the five algorithms are used to detect the southern boundary of the Gurbantunggut Desert in Xinjiang Uygur Autonomous Region of China, and the results show that the proposed algorithm has the best effect on real remote sensing image change detection. |
英文关键词 | change detection nonsubsampled contourlet transform Hidden Markov Tree model NSCT-HMT model FLICM |
类型 | Article |
语种 | 英语 |
国家 | Peoples R China ; New Zealand |
收录类别 | SCI-E |
WOS记录号 | WOS:000404553900111 |
WOS关键词 | UNSUPERVISED CHANGE DETECTION ; MULTITEMPORAL SAR IMAGES ; TRANSFORM |
WOS类目 | Chemistry, Analytical ; Engineering, Electrical & Electronic ; Instruments & Instrumentation |
WOS研究方向 | Chemistry ; Engineering ; Instruments & Instrumentation |
来源机构 | 新疆大学 |
资源类型 | 期刊论文 |
条目标识符 | http://119.78.100.177/qdio/handle/2XILL650/202416 |
作者单位 | 1.Xinjiang Univ, Coll Informat Sci & Engn, Urumqi 830046, Peoples R China; 2.Shanghai Jiao Tong Univ, Inst Image Proc & Pattern Recognit, Shanghai 200400, Peoples R China; 3.Auckland Univ Technol, Knowledge Engn & Discovery Res Inst, Auckland 1020, New Zealand |
推荐引用方式 GB/T 7714 | Chen, Pengyun,Zhang, Yichen,Jia, Zhenhong,et al. Remote Sensing Image Change Detection Based on NSCT-HMT Model and Its Application[J]. 新疆大学,2017,17(6). |
APA | Chen, Pengyun,Zhang, Yichen,Jia, Zhenhong,Yang, Jie,&Kasabov, Nikola.(2017).Remote Sensing Image Change Detection Based on NSCT-HMT Model and Its Application.SENSORS,17(6). |
MLA | Chen, Pengyun,et al."Remote Sensing Image Change Detection Based on NSCT-HMT Model and Its Application".SENSORS 17.6(2017). |
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