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An integrated photonic circuit architecture to perform a modified-convolution operation based on the Discrete Fractional Fourier Transform (DFrFT) is introduced. This is accomplished by utilizing two nonuniformly-coupled waveguide lattices…
Multimode optical fibers (MMFs) have gained renewed interest in the past decade, emerging as a way to boost optical communication data-rates in the context of an expected saturation of current single-mode fiber-based networks. They are also…
We introduce a novel Multi-modal Guided Real-World Face Restoration (MGFR) technique designed to improve the quality of facial image restoration from low-quality inputs. Leveraging a blend of attribute text prompts, high-quality reference…
In today's information age, advanced fiber optic transmission technology is of paramount importance. Multimode fibers (MMFs) using space-division multiplexing (SDM) are promising for improved transmission capacity, connection flexibility,…
In this letter, we present a genetic algorithm-based approach for image retrieval through a multimode fiber in a reference-less system. Due to mode interference, when an image is illuminated at one side of a multimode fiber, the transmitted…
Recovering the 3D shape of transparent objects using a small number of unconstrained natural images is an ill-posed problem. Complex light paths induced by refraction and reflection have prevented both traditional and deep multiview stereo…
We derive a new 3D model for magnetic particle imaging (MPI) that is able to incorporate realistic magnetic fields in the reconstruction process. In real MPI scanners, the generated magnetic fields have distortions that lead to deformed…
Over the past decade, reflection matrix microscopy (RMM) and advanced image reconstruction algorithms have emerged to address the fundamental imaging depth limitations of optical microscopy in thick biological tissues and complex media. In…
Recent development of lensless imagers has enabled three-dimensional (3D) imaging through a thin piece of optics in close proximity to a camera sensor. A general challenge of wide-field lensless imaging is the high computational complexity…
The lensless endoscope (LE) is a promising device to acquire in vivo images at a cellular scale. The tiny size of the probe enables a deep exploration of the tissues. Lensless endoscopy with a multicore fiber (MCF) commonly uses a spatial…
Non-invasive morphological assessment is the cornerstone of oocyte and embryo selection in assisted reproductive technology, yet clinical practice remains limited by two-dimensional, qualitative microscopy. While three-dimensional (3D)…
Direct automatic segmentation of objects from 3D medical imaging, such as magnetic resonance (MR) imaging, is challenging as it often involves accurately identifying a number of individual objects with complex geometries within a large…
We report on the development of a compact (volume $\approx$ 100\:cm$^3$), multimode diffraction-limited Raman spectrograph and probe designed to be compact as possible. The spectrograph uses `off the shelf' optics, a custom 3D-printed…
Endoluminal endoscopic procedures are essential for diagnosing colorectal cancer and other severe conditions in the digestive tract, urogenital system, and airways. 3D reconstruction and novel-view synthesis from endoscopic images are…
Deep learning-based methods have achieved promising results on surgical instrument segmentation. However, the high computation cost may limit the application of deep models to time-sensitive tasks such as online surgical video analysis for…
Light-field imaging facilitates the miniaturization of 3D cameras while it requires the extension of the depth-of-field (DoF) for practical applications such as endoscopy and intraoral scanning. Here we report a light-field camera (LFC)…
The formation of organized optical states in multidimensional systems is crucial for understanding light-matter interaction and advancing light-shaping technologies. Here, we report the observation of a self-localized, ultrafast pencil beam…
Dual-comb microscopy (DCM), an interesting imaging modality based on the optical-frequency-comb (OFC) mode and image pixel one-to-one correspondence, benefits from scan-less full-field imaging and simultaneous confocal amplitude and phase…
Deep learning has transformed computational imaging, but traditional pixel-based representations limit their ability to capture continuous, multiscale details of objects. Here we introduce a novel Local Conditional Neural Fields (LCNF)…
Recovering the physical attributes of an object's appearance from its images captured under an unknown illumination is challenging yet essential for photo-realistic rendering. Recent approaches adopt the emerging implicit scene…