Single-pixel imaging is a unique technique that can image target objects over a wide band range and in low-light environments. However, this method requires a large number of structured pattern illuminations in addition to reconstruction calculations, which limits its practical application. We introduce the single-pixel techniques that we have developed: deep learning, optimization, field-programmable gate array (FPGA), and nonnegative matrix factorization (NMF)-based methods. Deep learning and optimization techniques can improve image quality, and FPGA approaches can perform real-time imaging. The NMF approach can drastically reduce the number of structured patterns and measurement time.
KEYWORDS: Holograms, Computer generated holography, Algorithm development, Reconstruction algorithms, Light sources and illumination, Interpolation, Fluctuations and noise, 3D displays, 3D acquisition, Testing and analysis
Polygon-based computer-generated holography algorithms can achieve high realism at low computational cost. Many recent contributions improve the hologram generation efficiency and solve many issues of 3D realistic rendering. This manuscript provides a comprehensive evaluation of their performance and potential through a detailed classification and comparison. Although the numerical-based algorithms using spectral interpolation offer greater flexibility in achieving realistic 3D displays, further phase-optimization algorithms are needed to render 3D reconstructions with higher definition, reduced noise, and faster updates.
Diffraction calculations are essential in optics, including holography, optical element design, and information optics. Convolution-based diffraction calculations can be accelerated by Fourier transforms; however, they often suffer from ringing artifacts (a.k.a. Gibbs phenomena) due to the non-continuous borders of the calculation windows. Suppressing techniques for ringing artifacts have been proposed so far, but these techniques are time-consuming and use large amounts of memory. This study presents a ringing artifact reduction using the Fresnel integrals.
Color holographic displays typically independently manipulate and combine light for three different wavelengths. Recent advances have made it possible to jointly encode a single extended-phase spatial light modulator (SLM) pattern modulating all colors simultaneously to display holograms at higher framerates and qualities. However, this inevitably leads to “color replicas”, where the objects at one wavelength are replicated at different depths for different colors, leading to disturbances in the viewing experience, thereby limiting its usefulness for 3D displays. We propose a novel coded illumination scheme to decorrelate the different color signals, eliminating the color replicas. We present the novel joint-color coding CGH algorithm, as well as an additional calibration algorithm, showing significant improvements in visual quality with a minor modification to the optical display setup.
Spherical waves emanating from a point are usually modeled in wavefront recording planes perpendicular to their direction of propagation, leading to a symmetric wavefield, typically referred to as a point spread function (PSF). But when the wavefront recording plane is tilted with respect to the hologram plane, this wavefield becomes asymmetric and is typically obtained by the rotation of the frequency domain. This work aims to derive the asymmetric PSF (aPSF) analytically directly in the spatial domain, allowing for the accurate and efficient use of tilted wavefront recording planes in computer-generated holography.
We have developed a novel point-polygon hybrid method (PPHM) for calculating computer-generated holograms (CGHs), which takes advantage of both point-based and polygon-based methods. While point-based methods are good at presenting object details, polygon-based methods are good at efficiently rendering high-density surfaces with accurate occlusion. The PPHM algorithm combines the strengths of both methods and eliminates their weaknesses to achieve higher computational efficiency. It utilizes a low-polygon approximation of the original 3D polygonal meshes and leverages the computational advantages of the wavefront recording plane and look-up table methods to generate high-resolution holograms with smooth focal cues quickly. The proposed PPHM algorithm is validated to present continuous depth cues and accurate occlusion with fewer triangles, implying high computational efficiency without quality loss.
Accelerating computer-generated holograms (CGHs) is crucial for practical three-dimensional (3D) displays with electro-holography. The authors developed a fast CGH calculation algorithm that focuses on projecting only 3D wireframes because the formulas or algorithms for generating CGH become simpler and, in many cases, the expressivity of the wireframe is sufficient to provide users with all necessary information, such as which direction to move in a car navigation system. In this presentation, we provide an overview of how to accelerate the CGH calculation of wireframe art and discuss our future research directions with respect to the remaining issues.
Holography is the ultimate three-dimensional (3D) imaging technology, and research is actively being conducted on generating at high-speed holograms with enormous amounts of information and improving image quality. Because computer holography is based on wave optics algorithms, reconstructing the texture of 3D images is difficult. On the other hand, in principle, reconstructing texture in integral photography based on geometric optics is easy and the method is well established. We developed a high-performance special-purpose computer, called holographic reconstruction for ultra-realistic imaging, dedicated to the ray-wavefront conversion method. The design and implementation of the circuit for the hologram generation were performed using field-programmable gate array technology. Parallelization was performed at each step for increasing the speed of the calculation process. Furthermore, by sending output data directly to a displaying device in the high-definition multimedia interface, the communication between the host personal computer (PC) and special-purpose computer was controlled in one direction, which significantly reduced communication time. The system was ∼7.7 times faster than a PC alone and succeeded in the holographic reproduction of a textured 3D image in real time at 30 frames per second for a 1024 × 1024-pixel hologram.
Holographic displays have gained attention as ideal displays because of their advantageous properties for perfectly controlling light wavefronts. However, their realization is hindered by the considerable amount of computation required for large holograms. We developed special-purpose computers for holography using field-programmable gate arrays. In this paper, we discuss strategies for next generation special-purpose computers, in which we will implement an oriented-separable convolution, which can compute holograms at high speed. This algorithm has almost the same circuit configuration as that of the previous special-purpose computers and can speed up computation by two to three orders of magnitude. In addition, we describe herein a post-processing technique using deep learning in which low-precision holograms calculated using a special-purpose computer are converted to high-precision holograms via a simple deep neural network.
Digital holography is attracting attention because it can record instantaneous three-dimensional (3D) information and record dynamic phenomena. However, when recording high-speed phenomena, the frame rate ranges from tens of thousands to hundreds of millions, and the calculation time of the reconstructed images is a problem. We have developed a special-purpose computer for high-speed 3D imaging using digital holography. The developed special-purpose computer has four calculation modules and has achieved a calculation time 68 times faster than that of a personal computer with 48 cores. With the developed computer, a total of 32 reconstructed images can be calculated in 0.69 ms from four holograms of 128 × 128 pixels with eight varying depths.
We can record digitally-designed information of three-dimensional (3D) objects or optical elements on a holographic photosensitive material by using wavefront printing technology. But the hologram data generated from the digitally-designed information are very huge and there are often the occurrences of the unnecessary bidirectional communications. To solve this problem, we studied on a special-purpose computer for wavefront printing technology. This technique consists of generating the light-ray information from digitally-designed information of 3D objects, converting the light-ray information to the wavefront information and generating the hologram data locally from the wavefront information in interaction. In this paper, we designed the emulator of the special-purpose computer for wavefront printing technology and obtained the amount of information (the number of bits) required for the circuit by comparing the 3D images reconstructed from the holograms generated by the emulator. As a result, the amount of information of the wavefront information converted from the light-ray information most affected the quality of the 3D images reconstructed from the holograms generated by the emulator and we can design the emulator that can reduce the noise component from those 3D images. In the future, we will design the special-purpose computer for wavefront printing technology by using hardware description language and implement that special-purpose computer on a programmable logic device such as a field programmable gate array.
Creating computer-generated holograms (CGHs) is computationally costly, and many high-speed calculation algorithms have been proposed to address this problem. Recently, a calculation method using sparse point spread functions (PSFs) in the short-time Fourier transform (STFT) domain has been proposed. Since the PSFs are sparse in the STFT domain, only a small fraction of STFT coefficients need to be calculated. Further, in order to obtain the STFT coefficient, fast Fourier transform is generally necessary, but this new method can obtain the STFT coefficient by analytical means. This means that the number of calculations required can be greatly reduced. This paper describes the implementation of an STFTbased CGH calculation algorithm on a field-programmable gate array. All operations in this algorithm were implemented using fixed point arithmetic. Since this algorithm includes a trigonometric function and an error function, we used look-up tables (LUTs) to reduce calculation costs. We have devised a dedicated circuit architecture that allows parallel operations. As a secondary effect, a central processing unit was able to generate holograms using the STFT-based CGH calculation algorithm with fixed point arithmetic and LUTs, faster than by using floating point arithmetic.
One hologram calculation method is the random phase-free method. When this method is used for an amplitude hologram, a reproduced image with a high-quality image can be obtained. However, when the random phase-free method is used for the kinoform, the reproduced image is degraded. In this study, we applied the kinoform encoding method proposed by Li to the random phase-free method to improve the reproduced image. The effectiveness of the proposed method was compared with that of the conventional method via simulations and optical experiments. Additionally, the parameters were optimized by the simulations, and the effectiveness was verified by numerical experiments.
KEYWORDS: Computer generated holography, 3D modeling, 3D displays, Field programmable gate arrays, 3D image processing, Computing systems, Holography, 3D image reconstruction, Visualization, Telecommunications
Electro-holography is a prospective television technology for realizing photorealistic three-dimensional (3D) movies. However, the enormous computational power requirement for generating computer-generated holo- grams (CGHs) for digitally recording 3D information of the displayed image has been a barrier for the practical application of electro-holography. To solve this problem, our team has developed a dedicated computer for electro-holography, namely Holographic Reconstruction (HORN). HORN is a peripheral board-type computer comprising of field programmable gate arrays (FPGAs) and a PCI-express interface to configure cluster systems. In this paper, we introduced the detailed structure of HORN-8 and the implemented algorithms on it. Moreover, we discuss future prospects for improving its visual performance using executed experimental results.
To further accelerate the calculations associated with point-cloud-based holograms, wavelet shrinkage-based superpositIon (WASABI) has been proposed. Wavelet shrinkage eliminates the small wavelet coefficient values of the light distribution emitted from a point cloud, resulting in an approximated light distribution calculated from a few representative wavelet coefficients. Although WASABI can accelerate the hologram calculations, the approximated light distribution tends to lose the high-frequency components. To address this issue, random sampling was applied to the light distribution.
Electroholography enables the projection of three-dimensional (3-D) images using a spatial-light modulator. The extreme computational complexity and load involved in generating a hologram make real-time production of holograms difficult. Many methods have been proposed to overcome this challenge and realize real-time reconstruction of 3-D motion pictures. We review two real-time reconstruction techniques for aerial-projection holographic displays. The first reduces the computational load required for a hologram by using an image-type computer-generated hologram (CGH) because an image-type CGH is generated from a 3-D object that is located on or close to the hologram plane. The other technique parallelizes CGH calculation via a graphics processing unit by exploiting the independence of each pixel in the holographic plane.
We designed and developed a control circuit for a three-dimensional (3-D) light-emitting diode (LED) array to be used in volumetric displays exhibiting full-color dynamic 3-D images. The circuit was implemented on a field-programmable gate array; therefore, pulse-width modulation, which requires high-speed processing, could be operated in real time. We experimentally evaluated the developed system by measuring the luminance of an LED with varying input and confirmed that the system works appropriately. In addition, we demonstrated that the volumetric display exhibits different full-color dynamic two-dimensional images in two orthogonal directions. Each of the exhibited images could be obtained only from the prescribed viewpoint. Such directional characteristics of the system are beneficial for applications, including digital signage, security systems, art, and amusement.
We propose a simple gradation representation method for a reconstructed three-dimensional (3-D) image without controlling the brightness of the reference light. In the proposed method, we use multiple bit planes comprised of binary-weighted computer-generated holograms (CGHs) with various light transmittances. Binary-weighted CGH is generated by changing the white in the conventional binary CGH to gray. The light transmittance of a binary-weighted CGH is less than that of a conventional binary CGH. The object points of a 3-D object are assigned to multiple bit planes according to the gray level of the object points. The multiple bit planes are displayed sequentially in a time-division multiplex manner. Consequently, the proposed method realizes a gradation representation of a reconstructed 3-D object.
Microalgae have been receiving great attention for their ability to produce biomaterials that are applicable for food supplements, drugs, biodegradable plastics, and biofuels. Among such microalgae, Euglena gracilis has become a popular species by virtue of its capability of accumulating useful metabolites including paramylon and lipids. In order to maximize the production of desired metabolites, it is essential to find ideal culturing conditions and to develop efficient methods for genetic transformation. To achieve this, understanding and controlling cell-to-cell variations in response to external stress is essential, with chemically specific analysis of microalgal cells including E. gracilis. However, conventional analytical tools such as fluorescence microscopy and spontaneous Raman scattering are not suitable for evaluation of diverse populations of motile microalgae, being restricted either by the requirement for fluorescent labels or a limited imaging speed, respectively. Here we demonstrate video-rate label-free metabolite imaging of live E. gracilis using stimulated Raman scattering (SRS) – an optical spectroscopic method for probing the vibrational signatures of molecules with orders of magnitude higher sensitivity than spontaneous Raman scattering. Our SRS’s highspeed image acquisition (27 metabolite images per second) allows for population analysis of live E. gracilis cells cultured under nitrogen-deficiency - a technique for promoting the accumulation of paramylon and lipids within the cell body. Thus, our SRS system’s fast imaging capability enables quantification and analysis of previously unresolvable cell-to-cell variations in the metabolite accumulation of large motile E. gracilis cell populations.
Parallel calculations of large-pixel-count computer-generated holograms (CGHs) are suitable for multiple-graphics processing unit (multi-GPU) cluster systems. However, it is not easy for a multi-GPU cluster system to accomplish fast CGH calculations when CGH transfers between PCs are required. In these cases, the CGH transfer between the PCs becomes a bottleneck. Usually, this problem occurs only in multi-GPU cluster systems with a single spatial light modulator. To overcome this problem, we propose a simple method using the InfiniBand network. The computational speed of the proposed method using 13 GPUs (NVIDIA GeForce GTX TITAN X) was more than 3000 times faster than that of a CPU (Intel Core i7 4770) when the number of three-dimensional (3-D) object points exceeded 20,480. In practice, we achieved ∼40 tera floating point operations per second (TFLOPS) when the number of 3-D object points exceeded 40,960. Our proposed method was able to reconstruct a real-time movie of a 3-D object comprising 95,949 points.
Microbes, especially microalgae, have recently been of great interest for developing novel biofuels, drugs, and biomaterials. Imaging-based screening of live cells can provide high selectivity and is attractive for efficient bio-production from microalgae. Although conventional cellular screening techniques use cell labeling, labeling of microbes is still under development and can interfere with their cellular functions. Furthermore, since live microbes move and change their shapes rapidly, a high-speed imaging technique is required to suppress motion artifacts. Stimulated Raman scattering (SRS) microscopy allows for label-free and high-speed spectral imaging, which helps us visualize chemical components inside biological cells and tissues. Here we demonstrate high-speed SRS imaging, with temporal resolution of 0.14 seconds, of intracellular distributions of lipid, polysaccharide, and chlorophyll concentrations in rapidly moving Euglena gracilis, a unicellular phytoflagellate. Furthermore, we show that our method allows us to analyze the amount of chemical components inside each living cell. Our results indicate that SRS imaging may be applied to label-free screening of living microbes based on chemical information.
Random phase is required in computer-generated hologram (CGH) to widely diffuse object light and to avoid its concentration on the CGH; however, the random phase causes considerable speckle noise in the reconstructed image and degrades the image quality. We introduce a simple and computationally inexpensive method that improves the image quality and reduces the speckle noise by multiplying the object light with the designed convergence light. We furthermore propose the improved method of the designed convergence light with iterative method to reduce ringing artifacts. Subsequently, as the application, a lensless zoomable holographic projection is introduced.
KEYWORDS: Field programmable gate arrays, Microscopy, Image processing, Real time image processing, Optical imaging, Imaging systems, Cameras, Particles, Image resolution, Digital signal processing, Prototyping
High-speed imaging is an indispensable technique, particularly for identifying or analyzing fast-moving objects. The serial time-encoded amplified microscopy (STEAM) technique was proposed to enable us to capture images with a frame rate 1,000 times faster than using conventional methods such as CCD (charge-coupled device) cameras. The application of this high-speed STEAM imaging technique to a real-time system, such as flow cytometry for a cell-sorting system, requires successively processing a large number of captured images with high throughput in real time. We are now developing a high-speed flow cytometer system including a STEAM camera. In this paper, we describe our approach to processing these large amounts of image data in real time. We use an analog-to-digital converter that has up to 7.0G samples/s and 8-bit resolution for capturing the output voltage signal that involves grayscale images from the STEAM camera. Therefore the direct data output from the STEAM camera generates 7.0G byte/s continuously. We provided a field-programmable gate array (FPGA) device as a digital signal pre-processor for image reconstruction and finding objects in a microfluidic channel with high data rates in real time. We also utilized graphics processing unit (GPU) devices for accelerating the calculation speed of identification of the reconstructed images. We built our prototype system, which including a STEAM camera, a FPGA device and a GPU device, and evaluated its performance in real-time identification of small particles (beads), as virtual biological cells, owing through a microfluidic channel.
We report a high-speed parallel phase-shifting digital holography system using a special-purpose computer for image reconstruction. Parallel phase-shifting digital holography is a technique capable of single-shot phase-shifting interferometry. This technique records information of multiple phase-shifted holograms required for calculation of phase-shifting interferometry with a single shot by using space-division multiplexing. This technique needs image-reconstruction process for a huge amount of recorded holograms. In particular, it takes a long time to calculate light propagation based on fast Fourier transform in the process and to obtain a motion picture of a dynamically and fast moving object. Then we designed a special-purpose computer for accelerating the image-reconstruction process of parallel phase-shifting digital holography. We developed a special-purpose computer consisting of VC707 evaluation kit (Xilinx Inc.) which is a field programmable gate array board. We also recorded holograms consisting of 128 × 128 pixels at a frame rate of 180,000 frames per second by the constructed parallel phase-shifting digital holography system. By applying the developed computer to the recorded holograms, we confirmed that the designed computer can accelerate the calculation of image-reconstruction process of parallel phase-shifting digital holography ~50 times faster than a CPU.
KEYWORDS: Computer generated holography, Cameras, Remote sensing, 3D image reconstruction, Image sensors, 3D image processing, 3D displays, Integral imaging, Fourier transforms, Imaging systems
This paper shows the method to calculate a computer-generated hologram (CGH) for real scenes under natural light using a commercial light field camera, and shows the results of color reconstruction of the synthesized CGHs. The CGH calculation using light field camera is performed by converting four-dimensional light field captured with a light field camera into a complex amplitude distribution, and the converted complex amplitude distribution is propagated so as to generate an interference pattern. In color reconstruction, we calculated three CGHs with red, green and blue wavelengths and superposed reconstructed red, blue and green images to obtain reconstructed color images. We verified that color three-dimensional images were reconstructed by numerical and optical reconstructions of the synthesized CGHs.
We report frequency estimation of loudspeaker diaphragm vibrating at high speed by parallel phase-shifting digital holography which is a technique of single-shot phase-shifting interferometry. This technique records multiple phaseshifted holograms required for phase-shifting interferometry by using space-division multiplexing. We constructed a parallel phase-shifting digital holography system consisting of a high-speed polarization-imaging camera. This camera has a micro-polarizer array which selects four linear polarization axes for 2 × 2 pixels. We set a loudspeaker as an object, and recorded vibration of diaphragm of the loudspeaker by the constructed system. By the constructed system, we demonstrated observation of vibration displacement of loudspeaker diaphragm. In this paper, we aim to estimate vibration frequency of the loudspeaker diaphragm by applying the experimental results to frequency analysis. Holograms consisting of 128 × 128 pixels were recorded at a frame rate of 262,500 frames per second by the camera. A sinusoidal wave was input to the loudspeaker via a phone connector. We observed displacement of the loudspeaker diaphragm vibrating by the system. We also succeeded in estimating vibration frequency of the loudspeaker diaphragm by applying frequency analysis to the experimental results.
We have implemented a computer-generated hologram (CGH) calculation on Greatly Reduced Array of Processor Element with Data Reduction (GRAPE-DR) processors. The cost of CGH calculation is enormous, but CGH calculation is well suited to parallel computation. The GRAPE-DR is a multicore processor that has 512 processor elements. The GRAPE-DR supports a double-precision floating-point operation and can perform CGH calculation with high accuracy. The calculation speed of the GRAPE-DR system is seven times faster than that of a personal computer with an Intel Core i7-950 processor.
We have developed an algorithm which can record multiple two-dimensional (2-D) gradated projection patterns in a single three-dimensional (3-D) object. Each recorded pattern has the individual projected direction and can only be seen from the direction. The proposed algorithm has two important features: the number of recorded patterns is theoretically infinite and no meaningful pattern can be seen outside of the projected directions. In this paper, we expanded the algorithm to record multiple 2-D projection patterns in color. There are two popular ways of color mixing: additive one and subtractive one. Additive color mixing used to mix light is based on RGB colors and subtractive color mixing used to mix inks is based on CMY colors. We made two coloring methods based on the additive mixing and subtractive mixing. We performed numerical simulations of the coloring methods, and confirmed their effectiveness. We also fabricated two types of volumetric display and applied the proposed algorithm to them. One is a cubic displays constructed by light-emitting diodes (LEDs) in 8×8×8 array. Lighting patterns of LEDs are controlled by a microcomputer board. The other one is made of 7×7 array of threads. Each thread is illuminated by a projector connected with PC. As a result of the implementation, we succeeded in recording multiple 2-D color motion pictures in the volumetric displays. Our algorithm can be applied to digital signage, media art and so forth.
KEYWORDS: Computer generated holography, RGB color model, Diffraction, 3D image processing, Chromium, Near field diffraction, 3D displays, Visualization, 3D image reconstruction, Cameras
We propose acceleration of color computer-generated holograms (CGHs) from three-dimensional (3D) scenes that are expressed as texture (RGB) and depth (D) images. These images are obtained by 3D graphics libraries and RGB-D cameras: for example, OpenGL and Kinect, respectively. We can regard them as two-dimensional (2D) cross-sectional images along the depth direction. The generation of CGHs from the 2D cross-sectional images requires multiple diffraction calculations. If we use convolution-based diffraction such as the angular spectrum method, the diffraction calculation takes a long time and requires large memory usage because the convolution diffraction calculation requires the expansion of the 2D cross-sectional images to avoid the wraparound noise. In this paper, we first describe the acceleration of the diffraction calculation using “Band-limited double-step Fresnel diffraction,” which does not require the expansion. Next, we describe color CGH acceleration using color space conversion. In general, color CGHs are generated on RGB color space; however, we need to repeat the same calculation for each color component, so that the computational burden of the color CGH generation increases three-fold, compared with monochrome CGH generation. We can reduce the computational burden by using YCbCr color space because the 2D cross-sectional images on YCbCr color space can be down-sampled without the impairing of the image quality.
KEYWORDS: Computer generated holography, RGB color model, 3D image reconstruction, Holograms, Diffraction, Chromium, Digital holography, 3D image processing, Spatial light modulators, 3D displays
A calculation reduction method for color digital holography (DH) and computer-generated holograms (CGHs) using color space conversion is reported. Color DH and color CGHs are generally calculated on RGB space. We calculate color DH and CGHs in other color spaces for accelerating the calculation (e.g., YCbCr color space). In YCbCr color space, a RGB image or RGB hologram is converted to the luminance component (Y), blue-difference chroma (Cb), and red-difference chroma (Cr) components. In terms of the human eye, although the negligible difference of the luminance component is well recognized, the difference of the other components is not. In this method, the luminance component is normal sampled and the chroma components are down-sampled. The down-sampling allows us to accelerate the calculation of the color DH and CGHs. We compute diffraction calculations from the components, and then we convert the diffracted results in YCbCr color space to RGB color space. The proposed method, which is possible to accelerate the calculations up to a factor of 3 in theory, accelerates the calculation over two times faster than the ones in RGB color space.
We present a special-purpose computer named HORN (HOlographic ReconstructioN) for fast calculation of computer-
generated holograms (CGHs). The HORN can realize parallel processing of the CGH calculation by using field-
programmable gate arrays. The latest version of HORNs, HORN-7, can reconstruct holographic images more clearly than previous HORNs because HORN-7 can make CGHs as a phase-only hologram (kinoform). In addition, the HORN-
7 can directly output calculated CGHs on a spatial-light modulator via Digital Visual Interface. In this paper, we demonstrate real-time reconstruction of holographic motion pictures by the HORN-7. We calculated CGHs, which
consist of 1,920 × 1,080 pixels, from the object data of ~6,000 points, and succeeded in reconstructing holographic motion pictures from the calculated CGHs at the rate of ~7 frames per second.
We developed an electroholography unit for a three-dimensional display, which consists of a special-purpose c-omputational chip and a high minute reflective liquid-crystal display panel. We implemented them on one board whose size is approximately 28 cm x 13 cm. The chip can compute a computer-generated hologram whose size is 800 x 600 at nearly real time (0.15 s) for an object consisting of 400 points. After the calculation, the LCD panel displays the computer generated hologram made by the chip, and we can observe a three-dimensional (3D) motion image whose size is approximately 3 cm x 3 cm x 3 cm. The pixel pitch of the display panel is 12 μm, and the resolution is 800 x 600. To obtain a 3D motion image with large viewing zone and image size, we need to parallelize the unit. The unit can be readily scaled up, since the units consisting of the chip and the display are easily set in parallel
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