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The research and development of methods using of the specialized diffractive microstructure sensors embedded in the pattern of computer-generated holograms (CGH) manufactured on circular and X-Y laser writing systems is discussed. These microstructures consist of two parts: one of which is written before the CGH in the field of future hologram and the second one is written during the long-term writing of the CGH. The shift between the first and second part of the microstructure is the trace of the writing errors and allows one to determine and calculate the error of CGH fabrication along both orthogonal coordinates. The developed method is based on the principle of diffraction-based overlay with 1D and 2D built-in diffractive microstructure-sensors. Mathematical modeling and results of experimental test writings of such diffractive microstructure sensors are described. The efficiency of using these types of build-in sensors for the writing errors estimation for CGHs is demonstrated.

Herein, we have discussed three major methods which have been generally employed for the generation of optical beams with orbital angular momentum (OAM). These methods include the practice of diffractive optics elements (DOEs), metasurfaces (MSs), and photonic integrated circuits (PICs) for the production of in-plane and out-of-plane OAM. This topic has been significantly evolved as a result; these three methods have been further implemented efficiently by different novel approaches which are discussed as well. Furthermore, development in the OAM detection techniques has also been presented. We have tried our best to bring novel and up-to-date information to the readers on this interesting and widely investigated topic.

Efficiently generating 3D holograms is one of the most challenging research topics in the field of holography. This work introduces a method for generating multi‐depth phase‐only holograms using a fully convolutional neural network (FCN). The method primarily involves a forward–backward‐diffraction framework to compute multi‐depth diffraction fields, along with a layer‐by‐layer replacement method (L2RM) to handle occlusion relationships. The diffraction fields computed by the former are fed into the carefully designed FCN, which leverages its powerful non‐linear fitting capability to generate multi‐depth holograms of 3D scenes. The latter can smooth the boundaries of different layers in scene reconstruction by complementing information of occluded objects, thus enhancing the reconstruction quality of holograms. The proposed method can generate a multi‐depth 3D hologram with a PSNR of 31.8 dB in just 90 ms for a resolution of 2160 × 3840 on the NVIDIA Tesla A100 40G tensor core GPU. Additionally, numerical and experimental results indicate that the generated holograms accurately reconstruct clear 3D scenes with correct occlusion relationships and provide excellent depth focusing. This work introduces the forward–backward‐diffraction framework for computing multi‐depth diffraction fields and the layer‐by‐layer replacement method for handling occlusion relationships. When combined with a fully convolutional neural network, it generates multi‐depth holograms with excellent depth focusing and corrects occlusion relationships. The reconstructed scene exhibits minimal speckle noise and few edge artifacts.

We propose a compressive self-interference incoherent digital holography (SIDH) with a geometric phase metalens for section-wise holographic object reconstruction. We specify the details of the SIDH with a geometric phase metalens design that covers the visible wavelength band, analyze a spatial distortion problem in the SIDH and address a process of a compressive holographic section-wise reconstruction with analytic spatial calibration. The metalens allows us to realize a compressive SIDH system in the visible wavelength band using an image sensor with relatively low bandwidth. The operation of the proposed compressive SIDH is verified through numerical simulations.

Generating computer‐generated holograms (CGHs) for 3D scenes by learning‐based methods can reconstruct arbitrary 3D scenes with higher quality and faster speed. However, the homogenization and difficulty of obtaining 3D high‐resolution datasets seriously limit the generalization ability of the model. A novel approach is proposed to train 3D encoding models based on convolutional neural networks (CNNs) using 2D image datasets. This technique produces virtual depth (VD) images with a statistically uniform distribution. This approach employs a CNN trained with the angular spectrum method (ASM) for calculating diffraction fields layer by layer. A fully convolutional neural network architecture for phase‐only encoding, which is trained on the DIV2K‐VD dataset. Experimental results validate its effectiveness by generating a 4K phase‐only hologram within only 0.061 s, yielding high‐quality holograms that have an average PSNR of 34.7 dB along with an SSIM of 0.836, offering high quality, economic and time efficiencies compared to traditional methods. This study presents a novel method for generating computer‐generated holograms (CGHs) of 3D scenes using a CNN trained on 2D image datasets. By creating virtual depth (VD) images with a uniform statistical distribution, this approach enables fast reconstructions, achieving phase‐only holograms with an average PSNR of 34.7 dB and SSIM of 0.836, surpassing traditional techniques.

We present a novel approach for securing valuable documents using a complementary approach based on the encryption of computer-generated holograms (CGHs). The proposed approach utilizes the well-known iterative Fourier transform algorithm (IFTA) to generate a phase-only CGH for valuable digital and/or physical documents. The generated CGH is then secured by binary phase randomization, which is implemented using the symmetric encryption technique, exclusive OR (XOR). The reconstruction process for the calculated secured CGHs varied slightly depending on whether the documents were digital or physical. For digital documents, reconstruction was performed using a symmetric decryption key followed by an inverse Fourier transform (IFFT). On the other hand, the reconstruction of the physical document involved two additional processes: printing and scanning. To evaluate the quality of the digital reconstruction, the speckle signal-to-noise ratio (SSNR) was estimated for both printed grayscale and binary CGHs. The security analysis of the XOR-encrypted CGH was quantitatively evaluated to ensure the level of protection against various cryptographic attacks such as plaintext and brute-force attacks. The results revealed that the combination of phase CGHs and the XOR encryption/decryption provides robust cryptographic protection for valuable documents, benefiting document security and anti-counterfeiting.

The twin image problem, well known in Gabor holography, greatly obstructs the output of high-quality holograms. Previous solutions include numerical and instrumental means to eliminate or mitigate the issue. The proposed method demonstrates the feasibility of using the sagitta angle in a spherical reference beam as an intrinsic reference angle within in-line holography. Along with a miniaturized version of the object, to allow for a wide range of object sizes, from millimeters to meters, with a small variation within the original optical system. The inherent reference angle allows for a separation of the twin images in the reconstruction of a Gabor hologram, while maintaining the system on axis. Under lens-less Fourier criteria, the peripheral information of the visual field interferes with a spherical wave to generate an interference pattern that results in a hologram with separated images.

A novel four-image encryption scheme based on the quaternion Fresnel transforms (QFST), computer generated hologram and the two-dimensional (2D) Logistic-adjusted-Sine map (LASM) is presented. To treat the four images in a holistic manner, two types of the quaternion Fresnel transform (QFST) are defined and the corresponding calculation method for a quaternion matrix is derived. In the proposed method, the four original images, which are represented by quaternion algebra, are processed holistically in a vector manner by using QFST first. Then the input complex amplitude, which is constructed by the components of the QFST-transformed plaintext images, is encoded by Fresnel transform with two virtual independent random phase masks (RPM). In order to avoid sending entire RPMs to the receiver side for decryption, the RPMs are generated by utilizing 2D–LASM, which results that the amount of the key data is reduced dramatically. Subsequently, by using Burch’s method and the phase-shifting interferometry, the encrypted computer generated hologram is fabricated. To improve the security and weaken the correlation, the encrypted hologram is scrambled base on 2D–LASM. Experiments demonstrate the validity of the proposed image encryption technique.

The main problem faced by traditional three-dimensional (3D) holographic displays is the time-consuming and poor flexibility of the hologram generation process. To address this issue, this paper proposes a non-iterative 3D computer-generated hologram (SFS-ORAP-PC-3D) method based on single full-support optimized random phase and phase compensation. Combining the full-support optimized random phase (FS-ORAP) method and the 3D layer-based idea to efficiently and non-iteratively generate the phase-only hologram of a 3D object with arbitrary positions and sizes using single FS-ORAP, thus overcoming the limitations of the original ORAP method in target position and size. Meanwhile, using a Fresnel lens for phase compensation allows for free selection of reconstruction planes. Numerical and optical experiments validate the feasibility of our proposed method.

Holographic lithography in azobenzene-containing polymers has evolved from classical interference-based surface relief grating formation into a versatile platform for maskless, all-optical, and reconfigurable surface patterning. In its current iteration, this approach requires treating holography as a fully vectorial process, in which polarization is a design variable on the same level as the amplitude of the writing light field. Here we provide a perspective on the current status of vectorial holographic lithography in azomaterial films. We organize the phenomenology around the two limiting cases of surface deformations driven by structured polarization fields at nearly uniform intensity, and relief formation driven by structured intensity fields under nearly uniform polarization. We interpret both regimes within the emerging viscoplastic photoalignment framework, which coherently links molecular photoreorientation to a light-induced anisotropic stress tensor and to polarization-controlled stress pathways that can drive mass migration. Building on state-of-the-art implementations based on spatial light modulators, we outline routes toward holographic lithography with more complex structured light, where polarization, intensity, wavelength, and temporal dynamics could be co-designed within a higher-dimensional parameter space. We conclude by highlighting the main opportunities and challenges in the field. These include understanding and harnessing the non-linear morphological response of azomaterials, developing inverse design strategies for complex light fields, implementing in-situ optical metrology for real-time feedback and control, and scaling these approaches to larger areas. Progress along these directions could enable robust, predictive, and scalable lithographic workflows capable of patterning surfaces with multiple degrees of freedom of light.