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Imaging through scattering media using semidefinite programming.

Hui Chen1, Yesheng Gao1, Xingzhao Liu1

  • 1Shanghai Jiao Tong University, State Key Laboratory of Advanced Optical Communication Systems and Ne, China.

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|December 1, 2018
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Summary
This summary is machine-generated.

Researchers developed a new imaging method to recover clear images from scattering media. This technique combines least squares and semidefinite programming for precise image reconstruction, outperforming existing algorithms.

Keywords:
computational imagingphase retrievalscattering mediastructural similarity

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Area of Science:

  • Optics and Photonics
  • Image Processing
  • Computational Imaging

Background:

  • Imaging through scattering media, like turbid biological tissues, is challenging due to image degradation into speckle.
  • Recovering clear object images from scattered light is crucial for various applications.

Purpose of the Study:

  • To propose a novel method for reconstructing images from scattering media.
  • To enhance image clarity and accuracy compared to existing techniques.

Main Methods:

  • A two-stage approach: scattering characteristics (SCs) estimation and image reconstruction.
  • SCs estimation uses a least squares (LS) approach with a database of object-speckle pairs.
  • Image reconstruction involves solving a semidefinite programming (SDP) problem and extracting the largest rank-1 component.

Main Results:

  • The proposed method successfully reconstructs images from scattering media.
  • The Structural Similarity (SSIM) index was used to evaluate performance.
  • Achieved higher precision and superior reconstruction results compared to phase shift interferometry and single-shot phase retrieval algorithms.

Conclusions:

  • The combined LS and SDP method provides a precise and practical solution for imaging through scattering media.
  • Potential applications include biomedical imaging, scattering property measurement, and optical image encryption.