OPTICSAIFeb 21, 2025

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

arXiv:2502.15397v1h-index: 7
Originality Synthesis-oriented
AI Analysis

This incremental work addresses resolution limitations in holographic microscopy for biomedical diagnostics and materials science applications.

This study applied super-resolution techniques (RCAN and Real-ESRGAN) to enhance interferometric imaging in holographic microscopy, finding that RCAN provides superior numerical precision for phase map reconstruction while Real-ESRGAN improves visual quality and structural coherence.

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.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

Your Notes