Change Detection in SAR Images Based on the ROF Model Semi-Implicit Denoising Method
The explicit solution of the traditional ROF model in image denoising has the disadvantages of unstable results and requiring many iterations. To solve the problem, a new method, ROF model semi-implicit denoising, is proposed in this paper and applied to change detections of synthetic aperture radar...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2019-03-01
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| Series: | Sensors |
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| Online Access: | http://www.mdpi.com/1424-8220/19/5/1179 |
| _version_ | 1811277876766441472 |
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| author | Xuemei Lou Zhenhong Jia Jie Yang Nikola Kasabov |
| author_facet | Xuemei Lou Zhenhong Jia Jie Yang Nikola Kasabov |
| author_sort | Xuemei Lou |
| collection | DOAJ |
| description | The explicit solution of the traditional ROF model in image denoising has the disadvantages of unstable results and requiring many iterations. To solve the problem, a new method, ROF model semi-implicit denoising, is proposed in this paper and applied to change detections of synthetic aperture radar (SAR) images. All remote sensing images used in this article have been calibrated by ENVI software. First, the ROF model semi-implicit denoising method is used to denoise the remote sensing images. Second, for the denoised images, difference images are obtained by the logarithmic ratio and mean ratio methods. The final difference image is obtained by principal component analysis fusion (PCA fusion) of the two difference images. Finally, the final difference image is clustered by fuzzy local information C-means clustering (FLICM) to obtain the change regions. The research results show that the proposed method has high detection accuracy and time operation efficiency. |
| first_indexed | 2024-04-13T00:24:28Z |
| format | Article |
| id | doaj.art-6e7f89e0e52344179f5868fe95ac126b |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-04-13T00:24:28Z |
| publishDate | 2019-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-6e7f89e0e52344179f5868fe95ac126b2022-12-22T03:10:38ZengMDPI AGSensors1424-82202019-03-01195117910.3390/s19051179s19051179Change Detection in SAR Images Based on the ROF Model Semi-Implicit Denoising MethodXuemei Lou0Zhenhong Jia1Jie Yang2Nikola Kasabov3College of Information Science and Engineering, Xinjiang University, Urumuqi 830046, ChinaCollege of Information Science and Engineering, Xinjiang University, Urumuqi 830046, ChinaInstitute of Image Processing and Pattern Recognition, Shanghai Jiao Tong University, Shanghai 200240, ChinaKnowledge Engineering and Discovery Research Institute, Auckland University of Technology, Auckland 1020, New ZealandThe explicit solution of the traditional ROF model in image denoising has the disadvantages of unstable results and requiring many iterations. To solve the problem, a new method, ROF model semi-implicit denoising, is proposed in this paper and applied to change detections of synthetic aperture radar (SAR) images. All remote sensing images used in this article have been calibrated by ENVI software. First, the ROF model semi-implicit denoising method is used to denoise the remote sensing images. Second, for the denoised images, difference images are obtained by the logarithmic ratio and mean ratio methods. The final difference image is obtained by principal component analysis fusion (PCA fusion) of the two difference images. Finally, the final difference image is clustered by fuzzy local information C-means clustering (FLICM) to obtain the change regions. The research results show that the proposed method has high detection accuracy and time operation efficiency.http://www.mdpi.com/1424-8220/19/5/1179remote sensing imageROF model semi-implicit denoisingPCA fusionFLICMchange detection |
| spellingShingle | Xuemei Lou Zhenhong Jia Jie Yang Nikola Kasabov Change Detection in SAR Images Based on the ROF Model Semi-Implicit Denoising Method Sensors remote sensing image ROF model semi-implicit denoising PCA fusion FLICM change detection |
| title | Change Detection in SAR Images Based on the ROF Model Semi-Implicit Denoising Method |
| title_full | Change Detection in SAR Images Based on the ROF Model Semi-Implicit Denoising Method |
| title_fullStr | Change Detection in SAR Images Based on the ROF Model Semi-Implicit Denoising Method |
| title_full_unstemmed | Change Detection in SAR Images Based on the ROF Model Semi-Implicit Denoising Method |
| title_short | Change Detection in SAR Images Based on the ROF Model Semi-Implicit Denoising Method |
| title_sort | change detection in sar images based on the rof model semi implicit denoising method |
| topic | remote sensing image ROF model semi-implicit denoising PCA fusion FLICM change detection |
| url | http://www.mdpi.com/1424-8220/19/5/1179 |
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