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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Samadi, S. Cetin, M. Masnadi-Shirazi, M.A. |
| Copyright Year | 2004 |
| Abstract | Nonquadratic regularization-based image formation is a recently proposed framework for feature-enhanced radar imaging. Specific image formation techniques in this framework have so far focused on enhancing one type of feature, such as strong point scatterers, or smooth regions. However, many scenes contain a number of such feature types. We develop an image formation technique that simultaneously enhances multiple types of features by posing the problem as one of sparse representation based on combined dictionaries. This method is developed based on the sparse representation of the magnitude of the scattered complex-valued field, composed of appropriate dictionaries associated with different types of features. The multiple feature-enhanced reconstructed image is then obtained through a joint optimization problem over the combined representation of the magnitude and the phase of the underlying field reflectivities. |
| Sponsorship | IEEE Geoscience and Remote Sensing Society |
| Starting Page | 821 |
| Ending Page | 825 |
| Page Count | 5 |
| File Size | 393886 |
| File Format | |
| ISSN | 1545598X |
| Volume Number | 10 |
| Issue Number | 4 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2013-07-01 |
| Publisher Place | U.S.A. |
| Access Restriction | One Nation One Subscription (ONOS) |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Dictionaries Synthetic aperture radar Image reconstruction Radar polarimetry Image resolution Measurement Radar imaging synthetic aperture radar (SAR) Complex-valued imaging image reconstruction sparse signal representation |
| Content Type | Text |
| Resource Type | Article |
| Subject | Electrical and Electronic Engineering Geotechnical Engineering and Engineering Geology |
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