Super-Resolution for Interferometric Imaging: Model Comparisons and Performance Analysis

• URL: http://arxiv.org/abs/2502.15397v1
• Date: Fri, 21 Feb 2025 11:50:57 GMT
• Title: Super-Resolution for Interferometric Imaging: Model Comparisons and Performance Analysis
• Authors: Hasan Berkay Abdioglu, Rana Gursoy, Yagmur Isik, Ibrahim Cem Balci, Taha Unal, Kerem Bayer, Mustafa Ismail Inal, Nehir Serin, Muhammed Furkan Kosar, Gokhan Bora Esmer, Huseyin Uvet,
• Abstract summary: The study evaluates two Super-Resolution models, RCAN and Real-ESRGAN, for their effectiveness in reconstructing high-resolution interferograms from a microparticle-based dataset.<n>The results demonstrate that RCAN achieves superior numerical precision, making it ideal for applications requiring highly accurate phase map reconstruction.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: This study investigates the application of Super-Resolution techniques in holographic microscopy to enhance quantitative phase imaging. An off-axis Mach-Zehnder interferometric setup was employed to capture interferograms. The study evaluates two Super-Resolution models, RCAN and Real-ESRGAN, for their effectiveness in reconstructing high-resolution interferograms from a microparticle-based dataset. The models were assessed using two primary approaches: image-based analysis for structural detail enhancement and morphological evaluation for maintaining sample integrity and phase map accuracy. The results demonstrate that RCAN achieves superior numerical precision, making it ideal for applications requiring highly accurate phase map reconstruction, while Real-ESRGAN enhances visual quality and structural coherence, making it suitable for visualization-focused applications. This study highlights the potential of Super-Resolution models in overcoming diffraction-imposed resolution limitations in holographic microscopy, opening the way for improved imaging techniques in biomedical diagnostics, materials science, and other high-precision fields.

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