Holographic Data Research Articles

Computationally efficient processing of in situ underwater digital holograms

AbstractUnderwater digital in‐line holography can provide high‐resolution, in situ imagery of marine particles and offers many advantages over alternative measurement approaches. However, processing of holograms requires computationally expensive reconstruction and processing, and computational cost increases with the size of the imaging volume. In this work, a processing pipeline is developed to extract targets from holograms where target distribution is relatively sparse without reconstruction of the full hologram. This is motivated by the desire to efficiently extract quantitative estimates of plankton abundance from a data set (>300,000 holograms) collected in the Northwest Atlantic using a large‐volume holographic camera. First, holograms with detectable targets are selected using a transfer learning approach. This was critical as a subset of the holograms were impacted by optical turbulence, which obscured target detection. Then, target diffraction patterns are detected in the hologram. Finally, targets are reconstructed and focused using only a small region of the hologram around the detected diffraction pattern. A search algorithm is employed to select distances for reconstruction, reducing the number of reconstructions required for 1 mm focus precision from 1000 to 31. When compared with full reconstruction techniques, this method detects 99% of particles larger than 0.1 mm2, a size class which includes most copepods and larger particles of marine snow, and 85% of those targets are sufficiently focused for classification. This approach requires 1% of the processing time required to compute full reconstructions, making processing of long time‐series, large imaging volume holographic data sets feasible.

Fourier horizontal parallax only computer and digital holography of large size.

Registration and reconstruction of high-quality digital holograms with a large view angle are intensive computer tasks since they require the space-bandwidth product (SBP) of the order of tens of gigapixels or more. This massive use of SBP severely affects the storing and manipulation of digital holograms. In order to reduce the computer burden, this work focuses on the generation and reconstruction of very large horizontal parallax only digital holograms (HPO-DHs). It is shown that these types of holograms can preserve high quality and large view angle in x direction while keeping a low use of SBP. This work first proposes a numerical technique that allows calculating very large HPO-DHs with large pixel size by merging the Fourier holography and phase added stereogram algorithm. The generated Fourier HPO-DHs enable accurate storing of holographic data from 3D objects. To decode the information contained in these Fourier HPO-DHs (FHPO-DHs), a novel angular spectrum (AS) technique that provides an efficient use of the SBP for reconstruction is proposed. Our reconstruction technique, which is called compact space bandwidth AS (CSW-AS), makes use of cylindrical parabolic waves that solve sampling issues of FHPO-DHs and AS. Moreover, the CSW-AS allows for implementing zero-padding for accurate wavefield reconstructions. Hence, suppression of aliased components and high spatial resolution is possible. Notably, the imaging chain of Fourier HPO-DH enables efficient calculation, reconstruction and storing of HPO holograms of large size. Finally, the accuracy and utility of the developed technique is proved by both numerical and optical reconstructions.

Magnetic Holography and Its Application to Data Storage

The principle of magnetic holograms and its application to holographic memory are reviewed. A magnetic hologram was recorded through a thermomagnetic recording as a difference in magnetization direction and reconstructed with the magneto-optical effect. To achieve a bright reconstruction image, it is important to record deep magnetic fringes on the materials with large Faraday rotation coefficients. This technique was applied to the holographic memory using transparent magnetic garnets as a recording material. The first reconstruction image was dark and noisy, but improvements in the recording conditions resulted in error-free recording and reconstruction of the magnetic hologram. To form deep magnetic fringes, insertion of heat dissipation (HD) layers into recording layer was proposed. It was found that this HD multilayer medium showed diffraction efficiency higher than that of a single layer medium, and error-free recording and reconstruction were also achieved, using magnetic assisted recording. These results suggest that HD multilayer media have potential applications in recording media of magnetic holographic data storage. In future, a high recording density technique, such as multiple recording, should be developed.

Metasurface Holography in the Microwave Regime

Hologram technology has attracted a great deal of interest in a wide range of optical fields owing to its potential use in future optical applications, such as holographic imaging and optical data storage. Although there have been considerable efforts to develop holographic technologies using conventional optics, critical issues still hinder their future development. A metasurface, as an emerging multifunctional device, can manipulate the phase, magnitude, polarization and resonance properties of electromagnetic fields within a sub-wavelength scale, opening up an alternative for a compact holographic structure and high imaging quality. In this review paper, we first introduce the development history of holographic imaging and metasurfaces, and demonstrate some applications of metasurface holography in the field of optics. We then summarize the latest developments in holographic imaging in the microwave regime. These functionalities include phase- and amplitude-based design, polarization multiplexing, wavelength multiplexing, spatial asymmetric propagation, and a reconfigurable mechanism. Finally, we conclude briefly on this rapidly developing research field and present some outlooks for the near future.

Microplastic pollution monitoring with holographic classification and deep learning

The observation and detection of the microplastic pollutants generated by industrial manufacturing require the use of precise optical systems. Digital holography is well suited for this task because of its non-contact and non-invasive detection features and the ability to generate information-rich holograms. However, traditional digital holography usually requires post-processing steps, which is time-consuming and may not achieve the final object detection performance. In this work, we develop a deep learning-based holographic classification method, which computes directly on the raw holographic data to extract quantitative information of the microplastic pollutants so as to classify them according to the extent of the pollution. We further show that our method can generalize to the classification task of other micro-objects through cross-dataset validation. Without bulky optical devices, our system can be further developed into a portable microplastics detection system, with wide applicability in the monitoring of microplastic particle pollution in the ecological environment.

Dynamic sampling iterative phase retrieval for holographic data storage.

A dynamic sampling iterative phase retrieval method, which dynamically samples the Fourier intensity distribution of the reconstruction beam captured by the detector, is proposed to shorten the iterative number and decrease the phase error rate of phase retrieval in the phase-modulated holographic data storage. By the dynamic sampling method, that keeping relatively low frequency component of Fourier intensity spectrum at the beginning of iteration and gradually releasing more high frequency component at the subsequent iterations, we shortened the iterative number by 2 times and decreased the phase error rate to some extent because our method provided a better convergent path to the phase retrieval. We also believe the thought of our method can be used in more image retrieval fields.

Single-shot detection of four-level phase modulated signals using inter-pixel crosstalk for holographic data storage

We report a simple and stable phase detection method for holographic data storage systems. Our method needs only one image acquisition, and no additional light waves or interferometric measurements are required. The phase information is retrieved from intensities at pixel boundaries where inter-pixel crosstalk occurs owing to the spatial filtering in the Fourier plane of the input image. We numerically and experimentally demonstrate that our method can retrieve the phase signal with a sufficiently low error rate for holographic storage. We also compare the storage density of the proposed method to the conventional phase detection method.

Modeling and analysis of polarization effect on signal intensity profile of two-dimensional page data in holographic data storage system

The data transfer rate as well as recording data density of holographic data storage systems can be improved by using a high-numerical aperture (NA) objective lens. However, a high-NA lens is likely to develop an inhomogeneous intensity profile of a reproduced holographic page data based on the polarization state of reference and signal beams during recording and readout. We analytically formulated how the polarization state of reference and signal beams during recording and readout affects signal intensity on a camera over the entire area of the page data. When Born approximation is applicable, we found that the signal amplitude of the reproduced page data can be expressed by multiplying signal amplitude calculated from scalar diffraction theory by an attenuation coefficient dependent on the polarization state. This means the intensity profile of the page data, taking polarization effect into account, can be calculated without using vector diffraction theory which requires high computational complexity. The validity of this analytical formulation was confirmed through a comparison of experiments with numerical analysis. The formulation led to a new method of increasing signal intensity of the page data area deteriorated by the polarization effect.

GAN‐Holo: Generative Adversarial Networks‐Based Generated Holography Using Deep Learning

Current development in a deep neural network (DNN) has given an opportunity to a novel framework for the reconstruction of a holographic image and a phase recovery method with real‐time performance. There are many deep learning‐based techniques that have been proposed for the holographic image reconstruction, but these deep learning‐based methods can still lack in performance, time complexity, accuracy, and real‐time performance. Due to iterative calculation, the generation of a CGH requires a long computation time. A novel deep generative adversarial network holography (GAN‐Holo) framework is proposed for hologram reconstruction. This novel framework consists of two phases. In phase one, we used the Fresnel‐based method to make the dataset. In the second phase, we trained the raw input image and holographic label image data from phase one acquired images. Our method has the capability of the noniterative process of computer‐generated holograms (CGHs). The experimental results have demonstrated that the proposed method outperforms the existing methods.

Paper] Spatial Filter and Combination of Angle and Peristrophic Multiplexings to Achieve Recording Density of 1 Tbit/inch<sup>2</sup> in Holographic Data Storage

Paper] Spatial Filter and Combination of Angle and Peristrophic Multiplexings to Achieve Recording Density of 1 Tbit/inch<sup>2</sup> in Holographic Data Storage

Invited Paper] Investigation of Noise Characteristics of Multivalued Signals and Estimation of Single-page Storage Density in Holographic Data Storage

Invited Paper] Investigation of Noise Characteristics of Multivalued Signals and Estimation of Single-page Storage Density in Holographic Data Storage

Paper] Efficient Decoding Method for Holographic Data Storage Combining Convolutional Neural Network and Spatially Coupled Low-Density Parity-Check Code

Paper] Efficient Decoding Method for Holographic Data Storage Combining Convolutional Neural Network and Spatially Coupled Low-Density Parity-Check Code

Suitability analysis of holographic vs light field and 2D displays for subjective quality assessment of Fourier holograms.

Measuring the impact of compression on the reconstruction quality of holograms remains a challenge. A public subjectively-annotated holographic data set that allows for testing the performance of compression techniques and quality metrics is presented, in addition to a subjective visual quality assessment methodology. Moreover, the performance of the quality assessment procedures is compared for holographic, regular 2D and light field displays. For these experiments, a double-stimulus, multi-perspective, multi-depth testing methodology was designed and implemented. Analysis of the quality scores indicated that in the absence of a suitable holographic display and under the presented test conditions, non-holographic displays can be deployed to display numerically reconstructed holograms for visual quality assessment tasks.

Three-dimensional imaging from single-element holographic data.

We present a holographic imaging approach for the case in which a single source-detector pair is used to scan a sample. The source-detector pair collects intensity-only data at different frequencies and positions. By using an appropriate illumination strategy, we recover field cross correlations over different frequencies for each scan location. The problem is that these field cross correlations are asynchronized, so they have to be aligned first in order to image coherently. This is the main result of the paper: a simple algorithm to synchronize field cross correlations at different locations. Thus, one can recover full field data up to a global phase that is common to all scan locations. The recovered data are, then, coherent over space and frequency so they can be used to form high-resolution three-dimensional images. Imaging with intensity-only data is therefore as good as coherent imaging with full data. In addition, we use an ℓ1-norm minimization algorithm that promotes the low dimensional structure of the images, allowing for deep high-resolution imaging.

Non-interferometric phase retrieval for collinear phase-modulated holographic data storage

Because of its simple optical system setup and robust noise tolerance, non-interferometric phase retrieval is an important technique for phase-modulated holographic data storage. Usually, the iterative algorithm of non-interferometry needs hundreds of iteration numbers to retrieve phase accurately, the data transfer rate decreases severely. Strong constraints such as adding embedded data into the phase data page can reduce the iteration numbers, but this method decreases the code rate severely. In this paper, we proposed the advanced non-interferometric phase retrieval method based on the collinear system. By encoding the reference beam of the collinear optical holographic storage system with embedded data, the storage space of the signal beam data page is completely released and the encoding rate is doubled. The embedded data can provide more modulation index including phase and amplitude to shorten iterations, so the data transfer rate is also increased. In the simulation, we recorded a four-level phase pattern and retrieved the phase correctly.

Collinear non-interferometric phase retrieval for holographic data storage.

A collinear non-interferometric phase retrieval method for holographic data storage is proposed. The code rate of the collinear system can be increased by 2 times due to transferring the 50% embedded data from a signal beam to a reference beam. Because the reference beam should be always known both in the recording process and reading process, there is no extra material cost for saving the embedded data. Therefore, the storage density of collinear system is increased by about 2 times compared with previous off-axis non-interferometric phase retrieval systems. Besides, we can enhance the algorithm constraint to shorten iteration numbers by increasing the amplitude weight of the reference beam. In the experiment, we shortened the iteration number and the BER by about 3 times. We also find that the reference number can be reduced by using the collinear way and increasing the amplitude weight of reference. This law allows us to give more code positions to signal so that the data amount in one data page can be increased.

Multiplexed recording based on the reference wave correlation for computer-generated holographic data storage

Holographic data storage (HDS) based on a computer-generated hologram (CGH) technique has been proposed as a promising approach to realize an in-line and simple HDS system. This work focuses on multiplexed recording for CGH-based HDS, and the approach based on the reference wave correlation is introduced to the HDS. For the proposed method, the processes for a CGH design are modified to generate reference waves with different phase distributions for each recording. Since holograms are recorded to the same region in a medium with independent reference waves, recorded data-pages are selectively reconstructed by the corresponding reference wave illuminations. The experimental demonstration confirms the feasibility of the proposed method, and the theoretical characteristic for the number of recordable multiplexed holograms is estimated by the numerical simulation.

Doubling the acquisition rate by spatial multiplexing of holograms in coherent sparse coded aperture correlation holography.

Optical, spatial, or temporal multiplexing is a well-known approach to optimize the performance of imaging systems. Following the recent discovery about the capability to record a coherent hologram in an interferenceless working mode, we propose a motionless method to spatially multiplex more than one hologram in a single camera exposure. Using the rather simple multiplexing framework based on coded aperture correlation holography, we effectively increase the acquisition rate of dynamic scenes and the holographic data compression by two-fold. Quantitative or qualitative phase microscopy and acquisition of a bipolar hologram from a single camera shot, experimentally confirm the applicability of the suggested technique.

Computer-generated-hologram-based holographic data storage using common-path off-axis digital holography.

A reconstruction method for multilevel complex encoded data-pages is proposed to increase the recording density of computer-generated-hologram-based holographic data storage by using off-axis digital holography. Although the detection process is based on off-axis digital holography, the proposed method keeps the optical setup a simple and common-path configuration owing to the computer-generated holography. Five-level complex encoded data-pages can be experimentally reconstructed.

4‐ary 14/16 modulation code for reducing two‐dimensional inter‐symbol interference

Holographic data storage (HDS) can access data in a short amount of time and can also quickly transmit data because HDS records and reads data in units of pages. Thus HDS is regarded as a promising candidate for future optical recording storage systems. Conventional storage systems such as CD, DVD, and HDD have one-dimensional (1D) inter-symbol interference (ISI). However, HDS has a 2D ISI that degrades performance. In this study, to avoid and overcome the 2D-ISI problem, the authors propose a 14/16 modulation code for 4-ary HDS systems which represents 2 bits on each pixel. The proposed 14/16 modulation code allows a bit of unwanted ISI cases in order to raise the code rate, but it has a higher code rate but similar performance compared to a 3/4 modulation code that has no unwanted ISI cases.