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Feature Enhancement of Stripmap-Mode SAR Images Based on an Optimization Scheme

delete2009-10-01
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PRE
AI
C
Cheng-Yen Chiang *
陈
陈锟山 (Kun‐Shan Chen)
C
Chih‐Tien Wang
N
Nien-Shiang Chou
DOI：10.1109/LGRS.2009.2028038delete
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Abstract

Abstract

En 中文
Based on a nonquadratic-optimization method originally proposed for spotlight-mode SAR image reconstruction, a modification for stripmap-mode SAR images is presented in this letter. This is done by mathematically reformulating the projection kernel and numerically putting it into a form that is suitable for optimization. The performance was evaluated by measures of the target contrast and 3-dB beamwidth using Radarsat-1 data. Results were analyzed and compared with those using minimum-variance and multiple-signal-classification methods. Results demonstrate that the target's features are effectively enhanced and that the dominant scattering centers are well separated using the proposed method. In addition, the image fuzziness is greatly reduced, and the image fidelity is well preserved. The effectiveness of the modification is thus validated.
Keywords:
Feature enhancement
minimum variance (MV)
multiple signal classification (MUSIC)
stripmap SAR
synthetic aperture radar (SAR)

Journal

IEEE Geoscience and Remote Sensing Magazine cover
IEEE Geoscience and Remote Sensing Magazine
IF:
16.4
Papers:
1.0W
Citations:
5.1K

Organization

N
National Central University
Scholars:
1.0W
Papers: 8.5K
Citations: 6.4K
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