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Updated: Jun 26, 2026
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Digital Inline Holographic Microscopy (DIHM) of Weakly-scattering Subjects
Published on: February 8, 2014
Wiener reconstruction of undersampled imagery
Samuel T Thurman1, James R Fienup
1The Institute of Optics, University of Rochester, Rochester, New York 14627, USA. thurman@optics.rochester.edu
Summary
A new Fourier-domain Wiener filter reconstructs undersampled images by balancing sharpness, noise, and aliasing. This adaptable filter provides a net transfer function for imaging systems and reconstruction processes.
Area of Science:
- Image reconstruction
- Signal processing
- Digital imaging
Background:
- Undersampled imagery presents challenges in achieving high-quality reconstructions.
- Existing reconstruction methods often struggle to balance image sharpness, noise, and aliasing artifacts.
Purpose of the Study:
- To develop a novel Fourier-domain Wiener filter for improved undersampled image reconstruction.
- To enable adjustable trade-offs between reconstruction sharpness, noise amplification, and aliasing suppression.
Main Methods:
- Derivation of a Fourier-domain Wiener filter tailored for undersampled data.
- Development of a net transfer function encompassing imaging system and reconstruction effects.
- Analysis of the filter's performance across both aliased and unaliased spatial frequencies.
Main Results:
- A flexible Wiener filter allowing tunable reconstruction parameters.
- A comprehensive net transfer function applicable to various linear sharpening algorithms.
- Demonstrated capability to suppress aliasing artifacts while managing noise and enhancing sharpness.
Conclusions:
- The derived Wiener filter offers enhanced control over undersampled image reconstruction.
- The net transfer function provides a unified framework for analyzing imaging and reconstruction processes.
- This approach advances the field of digital image processing for undersampled data.
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