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Florian Willomitzer

Publications and source records attributed to Florian Willomitzer.

At least 19 recordsLinked to original sources
arXiv2026

Lensless wide-field 3D fiber endoscopy through scattering media using synthetic wavelength holography

Minimally invasive imaging with fiber optic endoscopes is crucial for in vivo visualization of tissue morphology, as it supports applications such as early detection of tumors. However, imaging performance of conventional fiber endoscopes is limited when scattering layers are present between target and the distal end of endoscope. This limitation is particularly relevant in biomedicine, where targets such as early stage lesions or blood clots can be obscured by scattering tissue. To address this challenge, we present a lensless endoscopic imaging approach based on synthetic wavelength holography (SWH). SWH is a computational imaging technique in which two optical fields acquired at closely spaced wavelengths are combined to synthesize a field at a longer synthetic wavelength. As the field at longer wavelengths is less sensitive to path length perturbations, this approach can enable endoscopic recovery of holographic information despite scattering in the intervening tissue. In addition, because the synthetic field is assembled from scattered optical fields with larger optical étendue, our approach can extend the field of view (FoV) beyond the numerical aperture of the fiber. In this paper, we present the first demonstration of an SWH-based lensless endoscope using a multicore multimode fiber. We experimentally recover three-dimensional images of objects hidden behind scattering layers and through real biological tissue, with a spatial resolution of $\approx 500~μm$. We further demonstrate recovery of object information over an extended FoV of 46° without any distal optics. These results suggest a practical path toward extending fiber endoscopy for wide-field, three-dimensional imaging through scattering media.

physics.optics↗
arXiv2026

Fast 360-Degree 3D Metrology for Directed Energy Deposition

Directed Energy Deposition (DED) is a metal additive manufacturing process capable of building and repairing large, complex metal parts from a wide range of alloys. Its flexibility makes it attractive for multiple industrial applications, e.g., in aerospace, automotive and biomedical fields. However, errors or defects introduced at any stage of the printing process can, if undetected, significantly impact the final result, rendering the printed part unusable. Potential in-situ correction methods of printing defects require fast and high-resolution on-the-fly 3D inspection inside the machine, but existing 3D monitoring methods often lack full 360° 3D coverage, require bulky setups, or are too slow for real-time layer-wise feedback. In this paper, we present a single-shot, multi-view polarized fringe projection profilometry (FPP) system designed for real-time in-situ 3D inspection during DED printing. Multiple camera-projector pairs are arranged around the deposition surface to measure depth from different viewpoints in single-shot, while cross-polarized image filtering suppresses specular reflections caused by varying surface reflectance across different alloys. The final 360° reconstruction is obtained via joint registration of the captured multi-view measurements. Our prototype has been deployed in a DED system and our first experiments demonstrate a depth precision better than $δz < 60\,μ\mathrm{m}$ on partially reflective and "shiny" metal surfaces, enabling accurate, layer-wise monitoring for closed-loop DED control.

physics.optics↗
arXiv2026

Synthetic Light-in-Flight

Light-in-flight (LiF) measurements enable the visualization of light paths through arbitrary, volumetric scenes, making light-matter interactions at ultrafast timescales visible. Traditionally, LiF measurements require specialized equipment, such as ultrashort pulse light sources and high-speed electronics, often limited by low spatial resolution. Herein, we introduce a novel computational approach, "Synthetic Light-in-Flight" (SLiF), that overcomes these constraints by relying solely on tunable, continuous wave (CW) lasers and off-the-shelf CMOS cameras. From multiple CW scene measurements at different optical wavelengths, we create multiple "synthetic fields," each at a "synthetic wavelength," which is the beat wave of two respective optical waves. These synthetic fields are robust to speckle and environmental fluctuations, enabling us to combine multiple synthetic fields into a "synthetic light pulse" that sections the volumetric scene at much lower instantaneous peak illumination power than a comparable physical light pulse. We experimentally demonstrate the generation of synthetic pulses with 1 ps-scale width and show that their complex synthetic pulse fields can be freely manipulated in the computer after their acquisition, allowing for spatial and temporal shaping of different sets of pulses from the same set of measurements to maximize the decoded information output for each scene. Finally, we show that the recovered time-of-flight information can be used to characterize physical scene properties, such as depth and refractive indices.

physics.optics↗
arXiv2026

Physics-informed Active Polarimetric 3D Imaging for Specular Surfaces

3D imaging of specular surfaces remains challenging in real-world scenarios, such as in-line inspection or hand-held scanning, requiring fast and accurate measurement of complex geometries. Optical metrology techniques such as deflectometry achieve high accuracy but typically rely on multi-shot acquisition, making them unsuitable for dynamic environments. Fourier-based single-shot approaches alleviate this constraint, yet their performance deteriorates when measuring surfaces with high spatial frequency structure or large curvature. Alternatively, polarimetric 3D imaging in computer vision operates in a single-shot fashion and exhibits robustness to geometric complexity. However, its accuracy is fundamentally limited by the orthographic imaging assumption. In this paper, we propose a physics-informed deep learning framework for single-shot 3D imaging of complex specular surfaces. Polarization cues provide orientation priors that assist in interpreting geometric information encoded by structured illumination. These complementary cues are processed through a dual-encoder architecture with mutual feature modulation, allowing the network to resolve their nonlinear coupling and directly infer surface normals. The proposed method achieves accurate and robust normal estimation in single-shot with fast inference, enabling practical 3D imaging of complex specular surfaces.

cs.CV↗
arXiv2025

Intensity-Correlation Synthetic Wavelength Imaging in Dynamic Scattering Media

Imaging through dynamic scattering media, such as biological tissue, presents a fundamental challenge due to light scattering and the formation of speckle patterns. These patterns not only degrade image quality but also decorrelate rapidly, limiting the effectiveness of conventional approaches, such as those based on transmission matrix measurements. Here, we introduce an imaging approach based on second-order correlations and synthetic wavelength holography (SWH) to enable robust image reconstruction through thick and dynamic scattering media. By exploiting intensity speckle correlations and using short-exposure intensity images, our method computationally reconstructs images from a hologram without requiring phase stability or static speckles, making it inherently resilient to phase noise. Experimental results demonstrate high-resolution imaging in both static and dynamic scattering scenarios, offering a promising solution for biomedical imaging, remote sensing, and real-time imaging in complex environments.

physics.optics↗
arXiv2025

Exploiting Phase Light Modulators for Low-SWaP Real-time Wavefront Correction at High-Resolution

Wavefront correction and beam tracking are critical in applications such as long-range imaging through turbulence and free-space optical communication. For instance, adaptive optics systems are employed to correct wavefront distortions caused by atmospheric turbulence and optical misalignments, while beam tracking systems maintain alignment between separate devices in free-space communication scenarios. Current state-of-the-art approaches offer several high-performance solutions, each tailored to specific correction tasks. However, integrating all these functionalities into a single device, e.g., for simultaneous adaptive wavefront correction and tracking, can significantly increase the size, weight, and power consumption (SWaP) of the final system. In this contribution, we demonstrate the use of the Texas Instruments Phase Light Modulator (PLM) as a low-SWaP, chip-scale solution for simultaneous wavefront correction and beam tracking in real-time, featuring over one million actuators. In particular, we will present and discuss multiple algorithms and optimization strategies that we have specifically developed for PLM-based wavefront correction.

physics.optics↗
arXiv2025

Event-based Motion-Robust Accurate Shape Estimation for Mixed Reflectance Scenes

Event-based structured light systems have recently been introduced as an exciting alternative to conventional frame-based triangulation systems for the 3D measurements of diffuse surfaces. Important benefits include the fast capture speed and the high dynamic range provided by the event camera - albeit at the cost of lower data quality. So far, both low-accuracy event-based and high-accuracy frame-based 3D imaging systems are tailored to a specific surface type, such as diffuse or specular, and can not be used for a broader class of object surfaces ("mixed reflectance scenes"). In this work, we present a novel event-based structured light system that enables fast 3D imaging of mixed reflectance scenes with high accuracy. On the captured events, we use epipolar constraints that intrinsically enable decomposing the measured reflections into diffuse, two-bounce specular, and other multi-bounce reflections. The diffuse surfaces in the scene are reconstructed using triangulation. Then, the reconstructed diffuse scene parts are leveraged as a "display" to evaluate the specular scene parts via deflectometry. This novel procedure allows us to use the entire scene as a virtual screen, using only a scanning laser and an event camera. The resulting system achieves fast and motion-robust (14Hz) reconstructions of mixed reflectance scenes with < 600 $μm$ depth error. Moreover, we introduce an "ultrafast" capture mode (250Hz) for the 3D measurement of diffuse scenes.

cs.CV↗
arXiv2025

Fiber Endoscopy Using Synthetic Wavelengths for 3D tissue imaging

Fiber-based endoscopes utilizing multi-core fiber (MCF) bundles offer the capability to image deep within the human body, making them well-suited for imaging applications in minimally invasive surgery or diagnosis. However, the optical fields relayed through each fiber core can be significantly affected by phase scrambling from height irregularities at the fiber ends or potential multi-mode cores. Moreover, obtaining high-quality endoscopic images commonly requires the fiber tip to be placed close to the target or relies on the addition of a lens. Additionally, imaging through scattering layers after the fiber tip is commonly not possible. In this work, we address these challenges by integrating Synthetic Wavelength Imaging (SWI) with fiber endoscopy. This novel approach enables the endoscopic acquisition of holographic information from objects obscured by scattering layers. The resulting endoscopic system eliminates the need for lenses and is inherently robust against phase scrambling caused by scattering and fiber bending. Using this technique, we successfully demonstrate the endoscopic imaging of features approximately 750micrometers in size on an object positioned behind a scattering layer. This advancement represents significant potential for enabling spatially resolved three-dimensional imaging of objects concealed beneath tissue using fiber endoscopes, expanding the capabilities of these systems for medical applications.

physics.optics↗
arXiv2024

Accurate Eye Tracking from Dense 3D Surface Reconstructions using Single-Shot Deflectometry

Eye-tracking plays a crucial role in the development of virtual reality devices, neuroscience research, and psychology. Despite its significance in numerous applications, achieving an accurate, robust, and fast eye-tracking solution remains a considerable challenge for current state-of-the-art methods. While existing reflection-based techniques (e.g., "glint tracking") are considered to be very accurate, their performance is limited by their reliance on sparse 3D surface data acquired solely from the cornea surface. In this paper, we rethink the way how specular reflections can be used for eye tracking: We propose a novel method for accurate and fast evaluation of the gaze direction that exploits teachings from single-shot phase-measuring-deflectometry(PMD). In contrast to state-of-the-art reflection-based methods, our method acquires dense 3D surface information of both cornea and sclera within only one single camera frame (single-shot). For a typical measurement, we acquire $>3000 \times$ more surface reflection points ("glints") than conventional methods. We show the feasibility of our approach with experimentally evaluated gaze errors on a realistic model eye below only $0.12^\circ$. Moreover, we demonstrate quantitative measurements on real human eyes in vivo, reaching accuracy values between only $0.46^\circ$ and $0.97^\circ$.

cs.CV↗
arXiv2024

Review and Novel Formulae for Transmittance and Reflectance of Wedged Thin Films on absorbing Substrates

Historically, spectroscopic techniques have been essential for studying the optical properties of thin solid films. However, existing formulae for both normal transmission and reflection spectroscopy often rely on simplified theoretical assumptions, which may not accurately align with real-world conditions. For instance, it is common to assume (1) that the thin solid layers are deposited on completely transparent thick substrates and (2) that the film surface forms a specular plane with a relatively small wedge angle. While recent studies have addressed these assumptions separately, this work presents an integrated framework that eliminates both assumptions simultaneously. In addition, the current work presents a deep review of various formulae from the literature, each with their corresponding levels of complexity. Our review analysis highlights a critical trade-off between computational complexity and expression accuracy, where the newly developed formulae offer enhanced accuracy at the expense of increased computational time. Our user-friendly code, which includes several classical transmittance and reflectance formulae from the literature and our newly proposed expressions, is publicly available in both Python and Matlab at this link.

cond-mat.mtrl-sci↗
arXiv2024

An Angular Spectrum Approach to Inverse Synthesis for the Characterization of Optical and Geometrical Properties of Semiconductor Thin Films

To design semiconductor-based optical devices, the optical properties of the used semiconductor materials must be precisely measured over a large band. Transmission spectroscopy stands out as an inexpensive and widely available method for this measurement but requires model assumptions and reconstruction algorithms to convert the measured transmittance spectra into optical properties of the thin films. Amongst the different reconstruction techniques, inverse synthesis methods generally provide high precision but rely on rigid analytical models of a thin film system. In this paper, we demonstrate a novel flexible inverse synthesis method that uses angular spectrum wave propagation and does not rely on rigid model assumptions. Amongst other evaluated parameters, our algorithm is capable of evaluating the geometrical properties of thin film surfaces, which reduces the variance caused by inverse synthesis optimization routines and significantly improves measurement precision. The proposed method could potentially allow for the characterization of "uncommon" thin film samples that do not fit the current model assumptions, as well as the characterization of samples with higher complexity, e.g., multi-layer systems.

physics.optics↗
arXiv2024

3D Imaging of Complex Specular Surfaces by Fusing Polarimetric and Deflectometric Information

Accurate and fast 3D imaging of specular surfaces still poses major challenges for state-of-the-art optical measurement principles. Frequently used methods, such as phase-measuring deflectometry (PMD) or shape-from-polarization (SfP), rely on strong assumptions about the measured objects, limiting their generalizability in broader application areas like medical imaging, industrial inspection, virtual reality, or cultural heritage analysis. In this paper, we introduce a measurement principle that utilizes a novel technique to effectively encode and decode the information contained in a light field reflected off a specular surface. We combine polarization cues from SfP with geometric information obtained from PMD to resolve all arising ambiguities in the 3D measurement. Moreover, our approach removes the unrealistic orthographic imaging assumption for SfP, which significantly improves the respective results. We showcase our new technique by demonstrating single-shot and multi-shot measurements on complex-shaped specular surfaces, displaying an evaluated accuracy of surface normals below $0.6^\circ$.

cs.CV↗
arXiv2023

Thermal Spread Functions (TSF): Physics-guided Material Classification

Robust and non-destructive material classification is a challenging but crucial first-step in numerous vision applications. We propose a physics-guided material classification framework that relies on thermal properties of the object. Our key observation is that the rate of heating and cooling of an object depends on the unique intrinsic properties of the material, namely the emissivity and diffusivity. We leverage this observation by gently heating the objects in the scene with a low-power laser for a fixed duration and then turning it off, while a thermal camera captures measurements during the heating and cooling process. We then take this spatial and temporal "thermal spread function" (TSF) to solve an inverse heat equation using the finite-differences approach, resulting in a spatially varying estimate of diffusivity and emissivity. These tuples are then used to train a classifier that produces a fine-grained material label at each spatial pixel. Our approach is extremely simple requiring only a small light source (low power laser) and a thermal camera, and produces robust classification results with 86% accuracy over 16 classes.

cs.CV↗
arXiv2023

Optimization-Based Eye Tracking using Deflectometric Information

Eye tracking is an important tool with a wide range of applications in Virtual, Augmented, and Mixed Reality (VR/AR/MR) technologies. State-of-the-art eye tracking methods are either reflection-based and track reflections of sparse point light sources, or image-based and exploit 2D features of the acquired eye image. In this work, we attempt to significantly improve reflection-based methods by utilizing pixel-dense deflectometric surface measurements in combination with optimization-based inverse rendering algorithms. Utilizing the known geometry of our deflectometric setup, we develop a differentiable rendering pipeline based on PyTorch3D that simulates a virtual eye under screen illumination. Eventually, we exploit the image-screen-correspondence information from the captured measurements to find the eye's rotation, translation, and shape parameters with our renderer via gradient descent. In general, our method does not require a specific pattern and can work with ordinary video frames of the main VR/AR/MR screen itself. We demonstrate real-world experiments with evaluated mean relative gaze errors below 0.45 degrees at a precision better than 0.11 degrees. Moreover, we show an improvement of 6X over a representative reflection-based state-of-the-art method in simulation.

cs.CV↗
arXiv2022

Single-shot ToF sensing with sub-mm precision using conventional CMOS sensors

We present a novel single-shot interferometric ToF camera targeted for precise 3D measurements of dynamic objects. The camera concept is based on Synthetic Wavelength Interferometry, a technique that allows retrieval of depth maps of objects with optically rough surfaces at submillimeter depth precision. In contrast to conventional ToF cameras, our device uses only off-the-shelf CCD/CMOS detectors and works at their native chip resolution (as of today, theoretically up to 20 Mp and beyond). Moreover, we can obtain a full 3D model of the object in single-shot, meaning that no temporal sequence of exposures or temporal illumination modulation (such as amplitude or frequency modulation) is necessary, which makes our camera robust against object motion. In this paper, we introduce the novel camera concept and show first measurements that demonstrate the capabilities of our system. We present 3D measurements of small (cm-sized) objects with > 2 Mp point cloud resolution (the resolution of our used detector) and up to sub-mm depth precision. We also report a "single-shot 3D video" acquisition and a first single-shot "Non-Line-of-Sight" measurement. Our technique has great potential for high-precision applications with dynamic object movement, e.g., in AR/VR, industrial inspection, medical imaging, and imaging through scattering media like fog or human tissue.

cs.CV↗
arXiv2022

Synthetic Wavelength Imaging -- Utilizing Spectral Correlations for High-Precision Time-of-Flight Sensing

This book chapter describes how spectral correlations in scattered light fields can be utilized for high-precision time-of-flight sensing. The chapter should serve as a gentle introduction and is intended for computational imaging scientists and students new to the fascinating topic of synthetic wavelength imaging. Technical details (such as detector or light source specifications) will be largely omitted. Instead, the similarities between different methods will be emphasized to "draw the bigger picture."

physics.optics↗
arXiv2022

Can Deep Learning Assist Automatic Identification of Layered Pigments From XRF Data?

X-ray fluorescence spectroscopy (XRF) plays an important role for elemental analysis in a wide range of scientific fields, especially in cultural heritage. XRF imaging, which uses a raster scan to acquire spectra across artworks, provides the opportunity for spatial analysis of pigment distributions based on their elemental composition. However, conventional XRF-based pigment identification relies on time-consuming elemental mapping by expert interpretations of measured spectra. To reduce the reliance on manual work, recent studies have applied machine learning techniques to cluster similar XRF spectra in data analysis and to identify the most likely pigments. Nevertheless, it is still challenging for automatic pigment identification strategies to directly tackle the complex structure of real paintings, e.g. pigment mixtures and layered pigments. In addition, pixel-wise pigment identification based on XRF imaging remains an obstacle due to the high noise level compared with averaged spectra. Therefore, we developed a deep-learning-based end-to-end pigment identification framework to fully automate the pigment identification process. In particular, it offers high sensitivity to the underlying pigments and to the pigments with a low concentration, therefore enabling satisfying results in mapping the pigments based on single-pixel XRF spectrum. As case studies, we applied our framework to lab-prepared mock-up paintings and two 19th-century paintings: Paul Gauguin's Poèmes Barbares (1896) that contains layered pigments with an underlying painting, and Paul Cezanne's The Bathers (1899-1904). The pigment identification results demonstrated that our model achieved comparable results to the analysis by elemental mapping, suggesting the generalizability and stability of our model.

cs.CV↗