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We introduce weighted feedback to improve iterative phase retrieval algorithms. This method accelerates convergence and enhances imaging contrast, offering a faster, high-quality solution for optical measurements.

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Area of Science:

  • Optics and Photonics
  • Computational Imaging
  • Metrology

Background:

  • Multiple distance phase retrieval offers cost-effective and compact imaging solutions.
  • The amplitude-phase retrieval algorithm (APR) provides stable, high-accuracy reconstruction but faces slow convergence and stagnation.
  • Efficient phase retrieval is crucial for advanced optical measurement techniques.

Purpose of the Study:

  • To address the slow convergence and stagnation issues in amplitude-phase retrieval algorithms.
  • To develop an enhanced iterative method for faster and more accurate phase retrieval.
  • To extend the applicability of multiple distance phase retrieval to less stringent illumination conditions.

Main Methods:

  • Proposed a novel iterative modality: weighted feedback.
  • Developed augmented algorithms: amplitude-phase retrieval with single feedback (APRSF) and double feedback (APRDF).
  • Experimentally validated the performance of APRSF and APRDF algorithms.

Main Results:

  • APRSF and APRDF algorithms demonstrated a 2x and 3x increase in convergence speed, respectively.
  • APRDF algorithm successfully extended multiple distance phase retrieval to partially coherent illumination.
  • Enhanced imaging contrast for both amplitude and phase was achieved with APRDF.

Conclusions:

  • Weighted feedback significantly improves the convergence speed of iterative phase retrieval.
  • The APRDF algorithm offers a robust and versatile solution for phase retrieval under relaxed light source requirements.
  • This work enables fast-converging, high-contrast imaging for iterative phase retrieval applications.