Superresolution imaging using constrained iterative deconvolution

Xiongjun Fu, Shuilian Peng, Shengqi Qian, Chengyan Zhang, Ming Xie, Shuguang Li

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Citation (Scopus)

Abstract

Constrained iterative deconvolution (CID) super-resolution algorithm and its fast version, i.e., fast constrained-iterative deconvolution (FCID) are studied. These approaches are able to break through the aperture limiting to angular resolutions and can be applicable to two-dimensional imaging of non-coherent radars. However, FCID algorithm suffers from divergence, which limits the improvement of angular resolutions. A cascade algorithm that FCID iterations alternate with CID iterations is developed in this paper. This algorithm significantly increases permissible FCID iterations, thus higher angular resolution of two-dimensional imaging is achieved with less computational burden.

Original languageEnglish
Title of host publicationProceedings of the 2016 IEEE 11th Conference on Industrial Electronics and Applications, ICIEA 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages669-672
Number of pages4
ISBN (Electronic)9781509026050
DOIs
Publication statusPublished - 19 Oct 2016
Event11th IEEE Conference on Industrial Electronics and Applications, ICIEA 2016 - Hefei, China
Duration: 5 Jun 20167 Jun 2016

Publication series

NameProceedings of the 2016 IEEE 11th Conference on Industrial Electronics and Applications, ICIEA 2016

Conference

Conference11th IEEE Conference on Industrial Electronics and Applications, ICIEA 2016
Country/TerritoryChina
CityHefei
Period5/06/167/06/16

Keywords

  • CID
  • FCID
  • cascade algorithm
  • higher angular resolution
  • less computational burden

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