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Applications and challenges of compressed imaging

  • ZHANG Hua ,
  • CAO Liangcai ,
  • JIN Guofan ,
  • David J. Brady
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  • 1. State Key Laboratory of Precision Measurement Technology and Instrument;Department of Precision Instruments, Tsinghua University, Beijing 100084, China;
    2. Department of Electronic and Computer Engineering, Duke University, Durham, North Carolina 27708, USA

Received date: 2018-04-20

  Online published: 2018-05-22

Abstract

This paper reviews the development and the applications of the modern compressive imaging in the whole electromagnetic spectra from the perspective of the marginal cost. The values of the compressive imaging need to be considered in the perspective of the hardware cost and the computational expense when the compressive models and the reconstruction algorithms are designed. Based on the plenoptic function, a couple of successful applications are presented to show the advantages in compressing different data. The challenges of the compressive imaging are presented in practical applications. For the large-scale applications of compressive imaging, it is a challenging task to design a compressed sensing model with high stability and good compatibility.

Cite this article

ZHANG Hua , CAO Liangcai , JIN Guofan , David J. Brady . Applications and challenges of compressed imaging[J]. Science & Technology Review, 2018 , 36(10) : 20 -29 . DOI: 10.3981/j.issn.1000-7857.2018.10.003

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