Super-resolution imaging through a multimode fiber: the physical upsampling of speckle-driven

TL;DR

This paper demonstrates that leveraging the physical properties of speckle formation in multimode fibers enhances super-resolution imaging, improving reconstruction quality at high magnifications for minimally invasive endoscopy.

Contribution

It introduces a physically informed deep learning model that utilizes speckle interferometry to physically upsample low-resolution images, advancing super-resolution imaging techniques.

Findings

Physical speckle properties improve super-resolution reconstruction.

Physical upsampling complements data-driven methods effectively.

High magnification imaging quality is significantly enhanced.

Abstract

Following recent advancements in multimode fiber (MMF), miniaturization of imaging endoscopes has proven crucial for minimally invasive surgery in vivo. Recent progress enabled by super-resolution imaging methods with a data-driven deep learning (DL) framework has balanced the relationship between the core size and resolution. However, most of the DL approaches lack attention to the physical properties of the speckle, which is crucial for reconciling the relationship between the magnification of super-resolution imaging and the quality of reconstruction quality. In the paper, we find that the interferometric process of speckle formation is an essential basis for creating DL models with super-resolution imaging. It physically realizes the upsampling of low-resolution (LR) images and enhances the perceptual capabilities of the models. The finding experimentally validates the role played by the physical upsampling of speckle-driven, effectively complementing the lack of information in data-driven. Experimentally, we break the restriction of the poor reconstruction quality at great magnification by inputting the same size of the speckle with the size of the high-resolution (HR) image to the model. The guidance of our research for endoscopic imaging may accelerate the further development of minimally invasive surgery.