Search Results (229)

The imaging modalities of correlation-assisted techniques utilize the inherent information present in the spatial correlation of random intensity patterns for the successful reconstruction of object information. However, most correlation approaches focus only on the reconstruction of amplitude information, as it is a direct byproduct of the correlation, disregarding the phase information. Complex-field reconstruction requires additional experimental or computational schemes, alongside conventional correlation geometry. The resurgence of holography in recent times, with advanced digital techniques and the adoption of the full-field imaging potential of holography in correlation with imaging techniques, has paved the way for the development of various state-of-the-art approaches to correlation optics. This review article provides an in-depth discussion of the recent developments in speckle-correlation-assisted techniques by focusing on various quantitative imaging scenarios. Furthermore, the recent progress and application of correlation-assisted holographic imaging techniques are reviewed, along with its potential challenges. Full article

Against the backdrop of the rapid advancement of intelligent speech interaction and holographic display technologies, this paper introduces an interactive holographic display system. This paper applies 2D-to-3D technology to acquisition work and uses a Complex-valued Convolutional Neural Network Point Cloud Gridding (CCNN-PCG) algorithm to generate a computer-generated hologram (CGH) with depth information for application in point cloud data. During digital human hologram building, 2D-to-3D conversion yields high-precision point cloud data. The system uses ChatGLM for natural language processing and emotion-adaptive responses, enabling multi-turn voice dialogs and text-driven model generation. The CCNN-PCG algorithm reduces computational complexity and improves display quality. Simulations and experiments show that CCNN-PCG enhances reconstruction quality and speeds up computation by over 2.2 times. This research provides a theoretical framework and practical technology for holographic interactive systems, applicable in virtual assistants, educational displays, and other fields. Full article

The concurrent dissolution and early hydration of tricalcium aluminate (C₃A) and tetracalcium aluminoferrite (C₄AF) critically govern early-stage reaction dynamics in Portland cement systems. However, their mutual kinetic interactions during reaction, particularly sulfate-dependent modulation mechanisms, remain poorly understood. Using in-situ digital holographic microscopy (DHM), this study resolved their interaction mechanisms during co-dissolution in aqueous and sulfate-bearing environments. Results reveal asymmetric modulation: while C₄AF’s dissolution exhibited limited sensitivity to C₃A’s presence, C₃A’s kinetics were profoundly altered by C₄AF through sulfate-concentration-dependent pathways, which originated from two competing C₄AF-mediated mechanisms: (1) suppression via common-ion effects, and (2) acceleration through competitive sulfate species adsorption. These mechanistic insights would provide a roadmap for optimizing cementitious materials through optimized reaction pathways. Full article

Digital holography can capture and reconstruct 3D object information, making it valuable for biomedical imaging and materials science. However, traditional holographic reconstruction methods require the use of phase shift operation in the time or space domain combined with complex computational processes, which, to some extent, limits the range of application areas. The integration of deep learning (DL) advancements with physics-informed methodologies has opened new avenues for tackling this challenge. However, most of the existing DL-based holographic reconstruction methods have high model complexity. In this study, we first design a lightweight model with fewer parameters through the synergy of deep separable convolution and Swish activation function and then employ it as a teacher to distill a smaller student model. By reducing the number of network layers and utilizing knowledge distillation to improve the performance of a simple model, high-quality holographic reconstruction is achieved with only one hologram, greatly reducing the number of parameters in the network model. This distilled lightweight method cuts computational expenses dramatically, with its parameter count representing just 5.4% of the conventional Unet-based method, thereby facilitating efficient holographic reconstruction in settings with limited resources. Full article

Accurate and non-invasive optical metrology of transparent objects is essential in several commercial and research applications, from fluid dynamics to biomedical imaging. In this work, a digital holography approach for thickness measurement of glass plate and temperature mapping of candle flame is presented that leverages a double-field-of-view (FOV) configuration combined with high spatial bandwidth utilization (SBU). By capturing a multiplexed hologram from two distinct objects in a single shot, the system overcomes the limitations inherent to single-view holography, enabling more comprehensive object information of thickness measurement and temperature-induced refractive index variations. The method integrates double-FOV digital holography with high SBU, allowing for accurate surface profiling and mapping of complex optical path length changes caused by temperature gradients. The technique exhibits strong potential for applications in the glass industry and microfluidic thermometry, convection analysis, and combustion diagnostics, where precise thermal field measurements are crucial. This study introduces an efficient holographic framework that advances the capabilities of non-contact measurement applications by integrating double-FOV acquisition into a single shot with enhanced spatial bandwidth exploitation. The approach sets the groundwork for real-time, volumetric thermal imaging and expands the applicability of digital holography in both research and industrial settings. Full article

Label-free, high-throughput, and 3D morphological analysis of blood cells remains a major challenge in biomedical optics. In this study, we investigate this issue using flow cytometry with digital holographic microscopy (DHM) to enable real-time, label-free imaging of red blood cells (RBCs) and blood coagulation structures (BCSs) without the need for staining or chemical pretreatment. We demonstrate an approach for the automated quantification and statistical characterization of these cells using quantitative phase information reconstructed from digital holograms. Although established image processing techniques such as phase unwrapping and segmentation are used, this study presents, to the best of our knowledge, the first statistical characterization of the 3D morphological features of BCSs. This is particularly useful in analyzing the heterogeneous and complex 3D structures of BCSs, which are difficult to assess using conventional microscopy. The results suggest that this DHM-based flow cytometry system provides a promising platform for non-invasive, real-time morphological evaluation of blood samples and has potential applications in hematological diagnostics and research related to blood coagulation. Full article

High-resolution holographic visualization of built environments remains largely inaccessible due to the complexity and technical demands of traditional 3D data acquisition processes. This study proposes a workflow for producing high-quality full-color digital holographic stereograms of architectural landmarks using Google Earth Studio. By leveraging photogrammetrically reconstructed three-dimensional (3D) city models and a controlled camera path, we generated perspective image sequences of two iconic monuments, that is, the Basílica de la Sagrada Família (Barcelona, Spain) and the Arc de Triomphe (Paris, France). A custom pipeline was implemented to compute keyframe coordinates, extract cinematic image sequences, and convert them into histogram data suitable for CHIMERA holographic printing. The holograms were recorded on Ultimate U04 silver halide plates and illuminated with RGB light-emitting diodes, yielding visually immersive reconstructions with strong parallax effects and color fidelity. This method circumvented the requirement for physical 3D scanning, thereby enabling scalable and cost-effective holography using publicly available 3D datasets. In conclusion, the findings indicate the potential of combining Earth Studio with digital holography for urban visualization, cultural heritage preservation, and educational displays. Full article

Traditional holographic printing techniques prove inadequate when only input data are available. Therefore, this paper proposes a new artificial-intelligence-based process for generating digital holographic stereograms from a single black-and-white photograph. This method eliminates the need for stereo cameras, photogrammetry, or 3D models. In this approach, a convolutional neural network and deep convolutional neural field model are used for image colorization and a depth-map estimation, respectively. Subsequently, the colored image and depth map are used to generate the multiview images required for creating holographic stereograms. This method efficiently preserves the visual characteristics of the original black-and-white images in the final digital holographic portraits. This provides a new and accessible method for holographic reconstruction using limited data, enabling the generation of 3D holographic content from existing images. Experiments were conducted using black-and-photographs of two historical figures, and highly realistic holograms were obtained successfully. This study has significant implications for cultural preservation, personal archiving, and the generation of life-like holographic images with minimal input data. By bridging the gap between historical photographic sources and modern holographic techniques, our approach opens up new possibilities for memory preservation and visual storytelling. Full article

Automatic focusing is a crucial research issue for achieving high-quality reconstructed images in digital holographic microscopy. This paper proposes an automatic focusing method that combines the discrete cosine transform (DCT) sparse dictionary with edge preservation index (EPI) criteria for off-axis digital holographic microscopy. Specifically, within a predefined search range, Fresnel transform is utilized to reconstruct the off-axis digital hologram, yielding reconstruction images at various reconstruction distances. Synchronously, the DCT sparse dictionary is employed to reduce speckle noise, and the EPI is calculated between the denoised image and original image. The value of EPI is used as an indicator for assessing the focal position. A single-peak focusing curve is obtained within the search range 10 mm, with a step size of 0.1 mm. Once the optimal focus position is determined, a focused and noise-reduced reconstructed image can be simultaneously achieved. Full article

We propose a pulsed modulated digital holographic microscopy (PM-DHM) technique for the dynamic measurement of flowing microparticles in microfluidic systems. By digitally tuning the pulse width and the repetition rate of a laser source within a single-frame exposure, this method enables the recording of multiple images of flowing microparticles at different time points within a single hologram, allowing the quantification of velocity and acceleration. We demonstrate the feasibility of PM-DHM by measuring the velocity, acceleration, and forces exerted on PMMA microspheres and red blood cells flowing in microfluidic chips. Compared to traditional frame-sampling-based imaging methods, this technique has a much higher time resolution (in a range of microseconds) that is limited only by the pulse duration. This method demonstrates significant potential for high-throughput label-free flow cytometry detection and offers promising applications in drug development and cell analysis. Full article

We present a single-capture multimodal bright-field (BF) and quantitative phase imaging (QPI) approach that enables the analysis of large, connected, or extended samples, such as confluent cell layers or tissue sections. The proposed imaging concept integrates a fiber-optic Mach–Zehnder interferometer-based off-axis digital holographic microscopy (DHM) with an inverted commercial optical BF microscope. Utilizing 8-bit grayscale dynamic range multiplexing, we simultaneously capture both BF images and digital holograms, which are then demultiplexed numerically via Fourier filtering, phase aberration compensation, and weighted image subtraction procedures. Compared to previous BF-DHM systems, our system avoids synchronization challenges caused by multiple image recording devices, improves acquisition speed, and enhances versatility for fast imaging of large, connected, and rapidly moving samples. Initially, we perform a systematic characterization of the system’s multimodal imaging performance by optimizing numerical as well as coherent and incoherent illumination parameters. Subsequently, the application capabilities are evaluated by multimodal imaging of living cells. The results highlight the potential of single-capture BF-DHM for fast biomedical imaging. Full article

Without using any optical lenses, lensless digital holography (LDH) records the hologram of a sample and numerically retrieves the amplitude and phase of the sample from the hologram. Such lensless imaging designs have enabled high-resolution and high-throughput imaging of specimens using compact, portable, and cost-effective devices to potentially address various point-of-care-, global health-, and telemedicine-related challenges. However, in lensless digital holography, the reconstruction results are severely affected by zero-order noise and twin images as only the hologram intensity can be recorded. To mitigate such interference and enhance image quality, extensive efforts have been made. In recent years, deep learning (DL)-based approaches have made significant advancements in the field of LDH reconstruction. It is well known that most deep learning networks are often regarded as black-box models, which poses challenges in terms of interpretability. Here, we present a deep unfolding network, dubbed the ISTAHolo-Net, for LDH reconstruction. The ISTAHolo-Net replaces the traditional iterative update steps with a fixed number of sub-networks and the regularization weights with learnable parameters. Every sub-network consists of two modules, which are the gradient descent module (GDM) and the proximal mapping module (PMM), respectively. The ISTAHolo-Net incorporates the sparsity-constrained inverse problem model into the neural network and hence combines the interpretability of traditional iterative algorithms with the learning capabilities of neural networks. Simulation and real experiments were conducted to verify the effectiveness of the proposed reconstruction method. The performance of the proposed method was compared with the angular spectrum method (ASM), the HRNet, the Y-Net, and the DH-GAN. The results show that the DL-based reconstruction algorithms can effectively reduce the interference of twin images, thereby improving image reconstruction quality, and the proposed ISTAHolo-Net performs best on our dataset. Full article

Holographic detection technology has found extensive applications in biomedical imaging, surface profilometry, vibration monitoring, and defect inspection due to its unique phase detection capability. However, the accuracy of quantitative holographic phase imaging is significantly affected by the interference from direct current and twin image terms. Traditional methods, such as multi-exposure phase shifting and off-axis holography, have been employed to mitigate these interferences. While off-axis holography separates spectral components by introducing a tilted reference beam, it inevitably induces phase disturbances that compromise measurement accuracy. This study provides a computational explanation for the incomplete phase compensation issue in existing algorithms and establishes precision criteria for phase compensation based on theoretical formulations. We propose two novel phase compensation methods—the non-iterative compensation approach and the multi-iteration compensation technique. The principles and applicable conditions of these methods are thoroughly elucidated, and their superiority is demonstrated through comparative experiments. The results indicate that the proposed methods effectively compensate for phase disturbances induced by the tilted reference beam, offering enhanced precision and reliability in quantitative holographic phase measurements. Full article

Digital Holographic Microscopy (DHM) is a method of converting hologram images into three-dimensional (3D) images by image processing, which enables us to obtain the detailed shapes of the objects to be observed. Three-dimensional imaging of the microscopic objects by DHM can contribute to the early diagnosis and the detection of the diseases in the medical field by observing the shape of the cells. DHM requires several experimental components. One of them is the laser, which is a problem because its high power may cause the deformation and the destruction of the cells and the death of the microorganisms. Since the greatest advantage of DHM is the detailed geometrical information of the object by 3D measurement, the loss of such information is a serious problem. To solve this problem, a Neutral Density (ND) filter has been used to reduce power after the laser irradiation. However, the image acquired by the image sensor becomes too dark to obtain sufficient information, and the effect of noise increased due to the decrease in the amount of light. Therefore, in this paper, we propose the Frame-Stacking Method (FSM) for dark DHM for reproducing 3D profiles that enable us to observe the shape of the objects from the images taken in low-power environments when the power is reduced. The proposed method realizes highly accurate 3D profiles by the frame decomposition of the low-power videos into images and superimposing and rescaling the obtained low-power images. On the other hand, the continuous irradiation of the laser beam for a long period may destroy the shape of the cells and the death of the microorganisms. Therefore, we conducted experiments to investigate the relationship between the number of superimposed images corresponding to the irradiation time and the 3D profile, as well as the characteristics of the power and the 3D profile. Full article

Digital Holographic Microscopy (DHM) is a technique that uses the phase information of light to generate a three-dimensional (3D) profile of an object. Recently, it has been utilized in various fields such as disease diagnosis and research on microorganisms. In the process in DHM, a narrow region around one of the sidebands from the frequency domain is windowed to avoid noise caused by the direct current (DC) term. However, it may not obtain the high-frequency information about the object. On the other hand, windowing a wide region increases the noise caused by the DC term, and generates the noise in the 3D profile. To solve this trade-off, we propose a noise reduction method using Kalman filter. From the recorded hologram image, we can create the frequency domain. It obtains multiple windowed sidebands centered on multiple pixels at random from the frequency domain. This creates a group of data in which noise is generated randomly. This is regarded as frequency series data, and Kalman filtering is performed. This method can reduce the noise caused by the DC term while acquiring high-frequency information. In addition, this method has the advantage that only one image is needed for frequency series data in the Kalman filter. The effectiveness of the proposed method is verified by comparison with conventional filtering methods and general image processing methods. The validation results prove the usefulness of the proposed method, and the proposed method is expected to have a significant effect on improving the accuracy of disease diagnosis techniques using DHM. Full article