Simple complex amplitude encoding of a phase-only hologram using binarized amplitude

We suggest the use of halftone images for the generation of phase-only Fresnel holograms. The hologram is calculated by spatial filtering in the frequency plain of the two-dimensional cosine Transform. The phase-only hologram is obtained by keeping in the hologram plane only the phase distribution of the inverse light propagation of the desired halftone image located in the reconstruction plane. No iterative method is used in the calculation.

We have analyzed several types of acoustical holograms similar to and including the phase-only hologram suggested by Metherell.1 The analyses have involved three different diffraction regions: the Fraunhofer, Fresnel, and very-near-field. Each type of hologram studied is characterized by discarding some part of the information present in the wave scattered by the object and recording the portion that is left, thus allowing more efficient use of the recording medium. (For example, in the phase-only hologram the phase information in the scattered wave is retained, but the amplitude information is discarded.) The object investigated in each case was a long slit, thereby confining the analyses to one dimension.

ABSTRACTThe success of data-driven deep learning in computational imaging is often constrained by the need for extensive labeled datasets. Recent progress in physics-informed neural networks has mitigated this issue by integrating analytical physical models, allowing data-free training. However, for challenging imaging tasks, such as to simultaneously acquire complex amplitude light-field information, the weak physical constraints of conventional imaging hardware largely limit the spatiotemporal imaging resolution. Here, we propose an extremely simple yet powerful monocular camera for complex amplitude imaging based on a liquid-crystal (LC)-lens-informed Fourier neural network. Combining a polarization-multiplexed bifocal LC lens with a polarization image sensor, the camera acts as a polarization phase-shifting radial shearing interferometer. Without any labeled data, the LC-lens-informed Fourier neural network can reconstruct the complex amplitude of a variety of scenes from captured polarization images in a single shot with high fidelity. We experimentally demonstrate the reconstruction of wavefront aberrations involving 136 Zernike modes with a phase accuracy of λ/35 as well as static hologram retrieval and dynamic monitoring of air flow and flame fields. This complementary hardware-algorithm framework offers a promising pathway for developing compact, versatile and high-performance complex amplitude imaging systems for adaptive optics, hologram reconstruction and material diagnosis applications.

Binary phase-only filters (BPOFs) have generated much study because of their implementation on currently available spatial light modulator devices. On polarization-rotating devices such as the magneto-optic SLM, it is also possible to encode binary amplitude information into two SLM transmission states, in addition to the binary phase information. This is done by varying the rotation angle of the polarization analyzer following the SLM in the optical train. Through this parameter, a continuum of filters may be designed that span the space of binary phase and amplitude filters (BPAFs) between BPOFs and binary amplitude filters. In this study, we investigate the design of optimal BPAFs for the key correlation characteristics of peak sharpness (through the PCE metric), SNR, and discrimination between in-class and out-of- class images. We present simulation results illustrating improvements obtained over conventional BPOFs, and trade-offs between the different performance criteria in terms of the filter design parameter.

Quantitative holographic imaging records and reconstructs the complex amplitude of a light field. Conventionally, it relies on an interferometric setup with a reference beam that is sensitive to external disturbances. This issue can be addressed by retrieving the complex field from diffracted intensity measurements using a non-interferometric system. However, existing techniques require multiple measurements or additional object support for complex amplitude reconstruction. This paper proposes NeuHolo, a non-interferometric holographic imaging framework based on the integration of neural field network and random phase modulation, which quantitatively estimates amplitude and phase from a single measurement by unsupervised deep learning without object support. Simultaneously, NeuHolo can automatically calibrate the physical parameters, further improving the robustness. We experimentally demonstrate that NeuHolo achieves high precision and large field of view in retrieving complex amplitude. Our study provides a powerful tool of 3D surface characterization for potential industrial applications.

Holograms are a promising technology for realizing a natural three-dimensional display. While the holographic pattern records both the phase and intensity information of an object, the spatial light modulator, which is a device for reproducing it, is capable of modulating either phase or amplitude. Therefore, in order to realize a perfect holographic image, a complex hologram must be converted into a phase-only hologram. Currently, SLM resolution is 4k or less, but resolution needs to be increased to achieve better quality holograms. This will increase the computational complexity of the Fourier transform, which is needed for each iterate. Therefore, a way to create a phase-only-hologram with a minimum number of iterations is needed. It is known that in the iterative method, the initial predicted value greatly affects the result. In this study, we propose a method to make initial guess to obtain more accurate phase only hologram with fewer iteration times. To obtain the initial guess, the desired image was divided into several parts, and the phaseonly hologram corresponding to each was obtained and added again. We used hybrid-input-output iteration to maximize the effect of pre-iterated guess. When iterates the same number of times, the peak signal-to-noise ratio (PSNR) value obtained by using proposed pre-iterated guess was higher than using the random initial guess. In other words, the desired PSNR value can be reached with a smaller number of iterations by using proposed method. After 15 iterations, proposed initial guess have ~0.3dB higher PSNR value, which means one or two times of reduced iterations.

This paper discusses an equivalent magnetic dipoles hybrid with artificial neural network method to reconstruct the noise source. The original near-field of the real source is obtained through the near-field scanning, and then the equivalent magnetic dipoles source is constructed to predict the radiation from the real source. The information of field's amplitude and phase is used to find the magnetic moment and locations of the equivalent dipoles. An iterative method combined with the artificial neural network is proposed for this purpose, where the origin field is continuously subtracted from the new field generated by equivalent magnetic dipoles. Through numerical and experimental results, the accuracy and efficiency of the proposed method are verified.

The combination of Computer-Generated Holography (CGH) and deep learning has opened the possibility to generate both real-time and high-quality holograms. However, the widely-used data-driven deep learning method faces the problem of the large number of labeled training datasets generated by traditional algorithms, such as Gerchberg–Saxton (GS) iterative algorithm. It always takes a long time and limits the training performance of the network. In this work, we propose a model-driven neural network for high-fidelity Phase-Only Hologram (POH) generation. The Fresnel diffraction process is introduced as the physical model, which makes the network can automatically learn the latent encodings of POHs in an unsupervised way. Furthermore, the sub-pixel convolution upsampling method effectively improves the reconstruction quality. Once the training is completed, the POH of any two-dimensional image can be quickly generated. The calculation time is one to two orders of magnitude faster.

Phase-shifting digital holography has been used for the study of vibrating objects. The time-averaged complex amplitude of Fresnel diffracted field due to a vibrating object was obtained by using a three-step phase-shifting algorithm. Taking the inverse Fresnel transform of the complex amplitude resulted in an image of the object superimposed with Bessel fringes. The Bessel fringes are contour map of the vibration amplitude. By sinusoidally modulating the phase of the reference beam at the vibration frequency, the brightest fringe could be shifted to points of interest, thus extending the measurable range of vibration amplitude.

We discuss necessary and sufficient conditions conducive to the reversal of nonlinear interaction in fiber optic transmission. While the complete information about complex amplitude and phase of the electric field certainly allows reversal of the nonlinear interaction, it is shown that knowledge about carriers' frequencies in WDM represents a sufficient condition for a successful compensation of the nonlinear impairment.

Imaging through scattering media using digital holography

The exact line-response function for scalar diffraction is found, valid at all distances from a diffracting plane. This is the complex amplitude in the field beyond an infinitesimal slit that is illuminated at normal incidence by a plane wave. The line response is quite simple and is easily evaluated numerically. It has an even simpler asymptotic form, which is accurate in the near field. The diffracted field beyond a plane at which the amplitude varies in one direction is found by convolving the line-response function with the complex amplitude in the plane.

Microwave imaging is one of the promising nondestructive testing (NDT) methods for porous radio-transparent composites when other testing methods are ineffective or not applicable. In this paper, the results of experiments on the microwave sounding of thermal insulation coatings for cryogenic fuel tanks provided by several aerospace companies are presented. The insulation samples represent a layer of radio-transparent porous polyurethane foam (PUF) glued onto a metal substrate and contain pre-produced defects imitating real PUF delamination. For the experiments, a setup designed for nondestructive testing of radio-transparent composites was used. The setup includes a compact radar emitting a continuous stepped-frequency signal in the range from 22.2 to 26.2 GHz, a two-coordinate electromechanical scanner with a platform for placing the samples under study, a microcontroller unit to synchronize the scanning and sounding procedures and a personal computer with the software for managing the experiments. Registering of the microwave holograms was performed by moving the sample under-study in the vicinity of a fixed antenna while measuring the complex amplitude of the electromagnetic field scattered by the sample. For the reconstruction of microwave holograms, the back propagation method based on the fast Fourier transform was used. To improve the contrast of defects against the background on the reconstructed images, the Butterworth bandpass filter was applied to the Fourier spectrum of the registered microwave hologram. The results of the PUF samples inner structure reconstruction in cases of single-frequency and broadband measurements are presented. It is shown that using broadband measurements allows reconstructing microwave images of the PUF defects with range resolution, which is unattainable when performing measurements at a single frequency. Obtaining range resolution enabled automatic focusing of the broadband microwave holograms: as the focusing criterion the depth corresponding to the maximum of holograms integral absolute amplitude was used.

In this paper, the basic principle of planar near field acoustic holography is expatiated and the reconstruction formula of sound source localization is given. We take theoretical results of sound pressure radiating from a point source to the holographic plane as the experimental data, and then substitute it in the reconstruction formula to reconstruct the sound source information. By changing holographic plane size, spacing and holographic measurement distance, we compared the sound source reconstruction results with the known sound source to see how these measured conditions parameters affect the reconstruction accuracy. Test results show that precise result can be got when the sound bandwidth exceed 5Khz, the hologram plane size is 6 times greater than the sound wavelength, the spacing of measurement point on holographic plane is less than 1/3 of the wavelength and the holographic measurement distance is less than 1/34 of the wavelength. We applied the planar near field acoustical holography in plant disease stress monitoring, and choose the signal with frequency of 2KHz to carry out the reconstruction experiment. The holographic plane was 0.6m side length square, measuring point spacing was 0.06m and the distance between hologram plane and reconstruction plane was 0.015m. Three sound sources were finally identified. By modifying the parameter setting and comparative analysis, we seek the best selection for simulation and use it as a reference in the ultrasonic signal tests of the diseases stressed plant. Having collected acoustic emission signals, we identified the sound source by near field acoustic holography and located plant diseases stress. Consequently, we can conduct a new crop disease forecast and precision spraying of pesticides.

The in-line configuration of DH makes use of the full pixel count in forming the holographic image, but the zero-order and the twin-image terms are superposed on the image. Phase-shifting digital holography (PSDH) is a very effective method of removing these terms, introduced by I. Yamaguchi, where the complex field at the hologram is obtained by phase-shifting interferometry [1]. From the complex field at the hologram plane, including the amplitude and phase information, the optical field at any other plane can be obtained by numerical diffraction.KeywordsPhase ShiftDigital HolographyPhase ProfileDigital HologramInterference IntensityThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.