Space-variant deconvolution for synthetic aperture imaging using simulated annealing

被引:0
|
作者
Robini, MC
Rastello, T
Vray, D
Magnin, IE
机构
关键词
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The synthetic aperture image formation process can be formulated as a space-variant 2D convolution. The recovery of the original reflection density is an ill-posed inverse problem which is both underdetermined and ill-conditionned. Its stabilization is achieved via concave stabilizers that are well adapted to the preservation of discontinuities. This leads to the minimization of a non-convex functional, a task which is successfully carried out using a Metropolis-type annealing algorithm. For improved performances, we investigate some inexpensive acceleration techniques which do not alter the theoretical convergence results; their efficiency is demonstrated through restorations from simulated data.
引用
下载
收藏
页码:432 / 435
页数:4
相关论文
共 50 条
  • [1] HIGHLY SPACE-VARIANT IMAGING-SYSTEM - OPTICAL-SIMULATION OF THE SYNTHETIC-APERTURE RADAR
    BURRIDGE, DA
    SMITH, RW
    JOURNAL OF THE OPTICAL SOCIETY OF AMERICA A-OPTICS IMAGE SCIENCE AND VISION, 1991, 8 (08) : 1195 - 1206
  • [2] Decomposition of Space-Variant Blur in Image Deconvolution
    Sroubek, Filip
    Kamenicky, Jan
    Lu, Yue M.
    IEEE SIGNAL PROCESSING LETTERS, 2016, 23 (03) : 346 - 350
  • [3] Blind image deconvolution using space-variant neural network approach
    Cheema, TA
    Qureshi, IM
    Hussain, A
    ELECTRONICS LETTERS, 2005, 41 (06) : 308 - 309
  • [4] Ill-posedness of space-variant image deconvolution
    Kieweg, Michael
    Gross, Herbert
    Sievers, Torsten
    Mueller, Lothar
    IMAGE RECONSTRUCTION FROM INCOMPLETE DATA VI, 2010, 7800
  • [5] Space-variant motion compensation for synthetic aperture radar under complicated flight path
    Huang, Penghui (huangpenghui@sjtu.edu.cn), 1600, SPIE (12):
  • [6] Space-variant motion compensation for synthetic aperture radar under complicated flight path
    Lu, Qianrong
    Huang, Penghui
    Gao, Yesheng
    Liu, Xingzhao
    JOURNAL OF APPLIED REMOTE SENSING, 2018, 12 (04):
  • [7] Deep learning for a space-variant deconvolution in galaxy surveys
    Sureau, F.
    Lechat, A.
    Starck, J. -L.
    ASTRONOMY & ASTROPHYSICS, 2020, 641
  • [8] SPACE-VARIANT KERNEL DECONVOLUTION FOR DUAL EXPOSURE PROBLEM
    Tallon, Miguel
    Mateos, Javier
    Babacan, S. Derin
    Molina, Rafael
    Katsaggelos, Aggelos K.
    19TH EUROPEAN SIGNAL PROCESSING CONFERENCE (EUSIPCO-2011), 2011, : 1678 - 1682
  • [9] Performance evaluation of image deconvolution techniques in space-variant astronomical imaging systems with nonlinearities
    Fliegel, Karel
    Janout, Petr
    Bednar, Jan
    Krasula, Lukas
    Vitek, Stanislav
    Svihlik, Jan
    Pata, Petr
    APPLICATIONS OF DIGITAL IMAGE PROCESSING XXXVIII, 2015, 9599