Shi, Yilei and Zhu, Xiao Xiang and Yin, Wotao and Bamler, Richard (2018) A fast and accurate basis pursuit denoising algorithm with application to super-resolving tomographic SAR. IEEE Transactions on Geoscience and Remote Sensing, 56 (10), pp. 6148-6158. IEEE - Institute of Electrical and Electronics Engineers. doi: 10.1109/TGRS.2018.2832721. ISSN 0196-2892.
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Official URL: https://ieeexplore.ieee.org/document/8412239
Abstract
L1 regularization is used for finding sparse solutions to an underdetermined linear system. As sparse signals are widely expected in remote sensing, this type of regularization scheme and its extensions have been widely employed in many remote sensing problems, such as image fusion, target detection, image super-resolution, and others, and have led to promising results. However, solving such sparse reconstruction problems is computationally expensive and has limitations in its practical use. In this paper, we proposed a novel efficient algorithm for solving the complex-valued L1 regularized least squares problem. Taking the high-dimensional tomographic synthetic aperture radar (TomoSAR) as a practical example, we carried out extensive experiments, both with the simulation data and the real data, to demonstrate that the proposed approach can retain the accuracy of the second-order methods while dramatically speeding up the processing by one or two orders. Although we have chosen TomoSAR as the example, the proposed method can be generally applied to any spectral estimation problems.
Item URL in elib: | https://elib.dlr.de/124193/ | ||||||||||||||||||||
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Document Type: | Article | ||||||||||||||||||||
Additional Information: | so2sat; relevancy 4; | ||||||||||||||||||||
Title: | A fast and accurate basis pursuit denoising algorithm with application to super-resolving tomographic SAR | ||||||||||||||||||||
Authors: |
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Date: | May 2018 | ||||||||||||||||||||
Journal or Publication Title: | IEEE Transactions on Geoscience and Remote Sensing | ||||||||||||||||||||
Refereed publication: | Yes | ||||||||||||||||||||
Open Access: | Yes | ||||||||||||||||||||
Gold Open Access: | No | ||||||||||||||||||||
In SCOPUS: | Yes | ||||||||||||||||||||
In ISI Web of Science: | Yes | ||||||||||||||||||||
Volume: | 56 | ||||||||||||||||||||
DOI: | 10.1109/TGRS.2018.2832721 | ||||||||||||||||||||
Page Range: | pp. 6148-6158 | ||||||||||||||||||||
Publisher: | IEEE - Institute of Electrical and Electronics Engineers | ||||||||||||||||||||
ISSN: | 0196-2892 | ||||||||||||||||||||
Status: | Published | ||||||||||||||||||||
Keywords: | L1 regularization, TomoSAR, basis pursuit denoising (BPDN), second order cone programming (SOCP), proximal gradient (PG) | ||||||||||||||||||||
HGF - Research field: | Aeronautics, Space and Transport | ||||||||||||||||||||
HGF - Program: | Space | ||||||||||||||||||||
HGF - Program Themes: | Earth Observation | ||||||||||||||||||||
DLR - Research area: | Raumfahrt | ||||||||||||||||||||
DLR - Program: | R EO - Earth Observation | ||||||||||||||||||||
DLR - Research theme (Project): | R - Vorhaben hochauflösende Fernerkundungsverfahren (old) | ||||||||||||||||||||
Location: | Oberpfaffenhofen | ||||||||||||||||||||
Institutes and Institutions: | Remote Sensing Technology Institute > EO Data Science Remote Sensing Technology Institute > Leitungsbereich MF | ||||||||||||||||||||
Deposited By: | Wang, Yuanyuan | ||||||||||||||||||||
Deposited On: | 05 Dec 2018 12:42 | ||||||||||||||||||||
Last Modified: | 08 Nov 2023 14:18 |
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