The DOI matches its Crossref record; 24 of the 24 references it cites were found in a registry or an index.
A detail-preserving scale-driven approach to change detection in multitemporal SAR images
Abstract
This paper presents a novel approach to change detection in multitemporal synthetic aperture radar (SAR) images. The proposed approach exploits a wavelet-based multiscale decomposition of the log-ratio image (obtained by a comparison of the original multitemporal data) aimed at achieving different scales (levels) of representation of the change signal. Each scale is characterized by a different tradeoff between speckle reduction and preservation of geometrical details. For each pixel, a subset of reliable scales is identified on the basis of a local statistic measure applied to scale-dependent log-ratio images. The final change-detection result is obtained according to an adaptive scale-driven fusion algorithm. Experimental results obtained on multitemporal SAR images acquired by the ERS-1 satellite confirm the effectiveness of the proposed approach.
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Cites
A theory for multiresolution signal decomposition: the wavelet representation
Mallat, S. G. (1989) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/34.192463 · Cited by 21,372
A Wavelet Tour of Signal Processing
(1999) · Elsevier eBooks · doi:10.1016/b978-0-12-466606-1.x5000-4 · Cited by 16,227
Ideal spatial adaptation by wavelet shrinkage
Donoho, D. L., & Johnstone, I. M. (1994) · Biometrika · doi:10.1093/biomet/81.3.425 · Cited by 8,760
The Laplacian pyramid as a compact image code
Burt, P., & Adelson, E. (1983) · IEEE Transactions on Communications · doi:10.1109/tcom.1983.1095851 · Cited by 6,077
Strang, G., & Nguyen, T. Q. (1996) · Cited by 4,180
Abe, S. (2001) · Springer eBooks · doi:10.1007/978-1-4471-0285-4 · Cited by 3,721
Digital Image Enhancement and Noise Filtering by Use of Local Statistics
Lee, J.-S. (1980) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.1980.4766994 · Cited by 2,728
Understanding Synthetic Aperture Radar Images
Oliver, C., & Quegan, S. (1998) · Cited by 1,811
Strang, G. (1996) · Wavelets · doi:10.1093/oso/9780195094237.003.0002 · Cited by 1,205
The Stationary Wavelet Transform and some Statistical Applications
Nason, G. P., & Silverman, B. W. (1995) · Lecture Notes in Statistics · doi:10.1007/978-1-4612-2544-7_17 · Cited by 1,122
Cited by
Earthquake Damage Assessment of Buildings Using VHR Optical and SAR Imagery
Brunner, D., Lemoine, G., & Bruzzone, L. (2010) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2009.2038274 · Cited by 586
Self-citationLiu, J., Gong, M., Qin, K., & Zhang, P. (2018) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2016.2636227 · Cited by 522
Metadata
- Authors
- Bovolo, F., & Bruzzone, L.
- Venue
- IEEE Transactions on Geoscience and Remote Sensing
- Published
- 2005-12
- Volume
- 43
- Issue
- 12
- Pages
- 2963-2972
- ISSN
- 0196-2892 (ISSN-L)
- OpenAlex
- W2152185773
- Cited by
- 406
- References
- 24
- FWCI
- 23.64
- Type
- journal article
- Language
- en
- Open access
- closed
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- Bovolo, F., & Bruzzone, L. (2005). A detail-preserving scale-driven approach to change detection in multitemporal SAR images. IEEE Transactions on Geoscience and Remote Sensing. https://doi.org/10.1109/tgrs.2005.857987
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