Joint L1-L2 Regularization for Inverse Scattering

被引:0
|
作者
Shah, Pratik [1 ]
Khankhoje, Uday K. [2 ]
Moghaddam, Mahta [1 ]
机构
[1] Univ So Calif, Elect Engn, Los Angeles, CA 90095 USA
[2] Indian Inst Technol Delhi, Elect Engn, New Delhi, India
关键词
D O I
暂无
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
We propose a method for a solution of the inverse electromagnetic scattering problem using both L1 and L2 norms as regularization. The applicability of the method is demonstrated for a two-dimensional (2D) microwave imaging problem using the Born-iterative Method(BIM) with synthetically generated data. Though a single L2 regularization can estimate the dielectric constant profile, the reconstruction (if and when it converges) is over-smoothed. Similarly, a single L1 regularization fails when the problem is ill-conditioned. We propose an optimization strategy where both the regularization parameters are estimated simultaneously. Different object shapes have been considered to evaluate the performance. The results indicate that the method can produce an accurate object localization and estimation of the dielectric constant.
引用
收藏
页码:868 / 869
页数:2
相关论文
共 50 条
  • [1] Inverse Scattering Using a Joint L1-L2 Norm-Based Regularization
    Shah, Pratik
    Khankhoje, Uday K.
    Moghaddam, Mahta
    [J]. IEEE TRANSACTIONS ON ANTENNAS AND PROPAGATION, 2016, 64 (04) : 1373 - 1384
  • [2] l1-l2 regularization of split feasibility problems
    Abdellatif Moudafi
    Aviv Gibali
    [J]. Numerical Algorithms, 2018, 78 : 739 - 757
  • [3] Iteratively reweighted l1-l2 norm minimization using wavelets in inverse scattering
    Sanghvi, Yash
    Bisht, Hrishitosh
    Gadre, V. M.
    Kulkarni, S., V
    [J]. JOURNAL OF THE OPTICAL SOCIETY OF AMERICA A-OPTICS IMAGE SCIENCE AND VISION, 2020, 37 (04) : 680 - 687
  • [4] L1-L2 Spatial Adaptive Regularization Method for Electrical Tomography
    Liu, Ziqi
    Xu, Yanbin
    Dong, Feng
    [J]. PROCEEDINGS OF THE 38TH CHINESE CONTROL CONFERENCE (CCC), 2019, : 3346 - 3351
  • [5] Joint L1-L2 Regularisation for Blind Speech Deconvolution
    Guan, Jian
    Wang, Xuan
    Xie, Zongxia
    Qi, Shuhan
    Wang, Wenwu
    [J]. ADVANCES IN MULTIMEDIA INFORMATION PROCESSING - PCM 2017, PT I, 2018, 10735 : 834 - 843
  • [6] Hyperspectral unmixing employing l1-l2 sparsity and total variation regularization
    Sun, Le
    Ge, Weidong
    Chen, Yunjie
    Zhang, Jianwei
    Jeon, Byeungwoo
    [J]. INTERNATIONAL JOURNAL OF REMOTE SENSING, 2018, 39 (19) : 6037 - 6060
  • [7] A REGULARIZATION IMAGING METHOD FOR FORWARD-LOOKING SCANNING RADAR VIA JOINT L1-L2 NORM CONSTRAINT
    Tan, Ke
    Li, Wenchao
    Huang, Yulin
    Yang, Jianyu
    [J]. 2017 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS), 2017, : 2314 - 2317
  • [8] 3-D inversion of magnetic data based on the L1-L2 norm regularization
    Utsugi, Mitsuru
    [J]. EARTH PLANETS AND SPACE, 2019, 71 (1):
  • [9] Identification of Multiple Hypoxia Signatures in Neuroblastoma Cell Lines by l1-l2 Regularization and Data Reduction
    Fardin, Paolo
    Cornero, Andrea
    Barla, Annalisa
    Mosci, Sofia
    Acquaviva, Massimo
    Rosasco, Lorenzo
    Gambini, Claudio
    Verri, Alessandro
    Varesio, Luigi
    [J]. JOURNAL OF BIOMEDICINE AND BIOTECHNOLOGY, 2010,
  • [10] SEM Resolution Improvement Using Semi-Blind Restoration with Hybrid L1-L2 Regularization
    Lin, Youzuo
    Kandel, Yudhishthir
    Zotta, Matthew
    Lifshin, Eric
    [J]. 2016 IEEE SOUTHWEST SYMPOSIUM ON IMAGE ANALYSIS AND INTERPRETATION (SSIAI), 2016, : 33 - 36