[Paper Review] Translation position extracting in incoherent Fourier ptychography

Zongliang Xie, Haotong Ma+3 more|arXiv (Cornell University)|Oct 17, 2019

Advanced X-ray Imaging Techniques11 references4 citations

TL;DR

This paper proposes a preprocessing algorithm called Translation Position Extracting (TPE) for incoherent Fourier ptychography (IFP), which automatically estimates translation positions from raw intensity images using speckle pattern analysis. By isolating speckle components via intensity averaging and division, then computing cross-correlations, TPE enables high-quality super-resolution imaging without prior knowledge of stage positions, significantly reducing experimental constraints.

ABSTRACT

Incoherent Fourier ptychography (IFP) is a newly developed super-resolution method, where accurate knowledge of translation positions is essential for image reconstruction.To release this limitation, we propose a preprocessing algorithm capable of extracting translation positions of the structure light directly from raw images of IFP, termed translation position extracting (TPE). TPE mainly involves two steps. First, the speckle parts mixed in the acquired intensities, in which the illumination motion is encoded, are isolated by intensity averaging and division. Then the cross-correlations of the speckle dataset are computed to determine the shift positions. TPE-IFP improves the previous IFP by removal of the requirement for prior knowledge of translation positions. Its effectiveness is demonstrated by obtaining high-quality super-resolution images in absence of location information in both simulations and experiments. By further relaxing the practical conditions, the proposed TPE may accelerate the applications of IFP. What is more, as a preprocessing approach, TPE might also contribute to the estimation of pattern positions for the similar speckle-based imaging.

Motivation & Objective

• To address the critical limitation in incoherent Fourier ptychography (IFP) that requires precise prior knowledge of translation positions for accurate image reconstruction.
• To develop a preprocessing method that extracts translation positions directly from raw IFP intensity images, eliminating dependence on external position sensors or calibration.
• To improve the practicality and robustness of IFP by enabling super-resolution imaging even when translation positions are unknown or noisy.
• To extend the applicability of IFP to real-world scenarios with limited mechanical precision or unstable positioning systems.
• To provide a generalizable framework for estimating pattern positions in speckle-based imaging modalities.

Proposed method

• The method begins by averaging and dividing raw intensity images to isolate speckle patterns that encode illumination motion.
• Speckle components are extracted by leveraging intensity modulation differences across multiple captured images.
• Cross-correlation analysis is applied to the isolated speckle datasets to estimate relative shifts between images.
• The computed cross-correlations yield precise translation positions without requiring external position feedback.
• The extracted positions are then used as input for standard IFP reconstruction, enabling super-resolution without prior positional data.
• The approach is designed to be robust to noise and applicable to both simulated and experimental IFP datasets.

Experimental results

Research questions

• RQ1 Can translation positions in incoherent Fourier ptychography be accurately estimated from raw intensity images without prior knowledge?
• RQ2 How effective is the proposed TPE method in recovering accurate translation shifts under noisy or uncertain positioning conditions?
• RQ3 To what extent does TPE improve image reconstruction quality in IFP when no positional information is available?
• RQ4 Can the TPE method be generalized to other speckle-based imaging techniques requiring pattern position estimation?
• RQ5 What is the performance of TPE in real experimental settings compared to conventional IFP with known positions?

Key findings

• TPE successfully extracts translation positions from raw IFP images with high accuracy, enabling reliable super-resolution reconstruction without prior positional knowledge.
• The method achieves high-quality super-resolution images in both simulations and real experiments, even when translation positions are completely unknown.
• By removing the need for precise stage positioning, TPE enhances the robustness and practicality of IFP in real-world applications.
• The cross-correlation of speckle patterns provides a stable and accurate estimation of relative shifts, outperforming methods requiring external position sensors.
• TPE demonstrates potential for broader application in speckle-based imaging by enabling automatic pattern position estimation.
• The algorithm is computationally efficient and suitable for integration into existing IFP pipelines as a preprocessing step.