Search Results (11)

In this work, we explored, for the first time, to the best of our knowledge, the potential of stochastic gradient descent (SGD) to optimize random phase functions for application in non-iterative phase-only hologram generation. We defined and evaluated four loss functions based on common image quality metrics and compared the performance of SGD-optimized random phases with those generated using Gerchberg–Saxton (GS) optimization. The quality of the reconstructed holograms was assessed through numerical simulations, considering both accuracy and computational efficiency. Our results demonstrate that SGD-based optimization can produce higher-quality phase holograms for low-contrast target scenes and presents nearly identical performance to GS-optimized random phases for high-contrast targets. Experimental validation confirmed the practical feasibility of the proposed method and its potential as a flexible alternative to conventional GS-based optimization. Full article

In this work, we explore an optimization idea for the complexity guidance of a phase retrieval solution for a single acquired hologram. This method associates free-space backpropagation with the fast iterative shrinkage-thresholding algorithm (FISTA), which incorporates an improvement in the total variation (TV) to guide the complexity of the phase retrieval solution from the complex diffracted field measurement. The developed procedure can provide excellent phase reconstruction using only a single acquired hologram. Full article

The optimization of imaging accuracy and speed is a crucial issue in the development of computer-generated holograms (CGH) for three-dimensional (3D) displays. This paper proposes an optimized iterative algorithm based on the angular spectrum method (ASM) to achieve high-quality holographic imaging across multiple planes. To effectively utilize spatial resources for multi-image reconstruction and mitigate the speckle noise caused by the overlapping of target images, constraint factors are introduced between different layers within the same region. The seeking rule of the constraint factor is also analyzed. By utilizing both constraint factors and variable factors, the presented method is able to calculate phase holograms for target figure imaging at four different planes. Simulation and experimental results demonstrate that the proposed method effectively improves the overall quality of the different planes, thus holding great potential for wide-ranging applications in the field of holography. Full article

It is very important for holographic optical tweezers (OTs) to develop high-quality phase holograms through calculation by using some computer algorithms, and one of the most commonly used algorithms is the Gerchberg–Saxton (GS) algorithm. An improved GS algorithm is proposed in the paper to further enhance the capacities of holographic OTs, which can improve the calculation efficiencies compared with the traditional GS algorithm. The basic principle of the improved GS algorithm is first introduced, and then theoretical and experimental results are presented. A holographic OT is built by using a spatial light modulator (SLM), and the desired phase that is calculated by the improved GS algorithm is loaded onto the SLM to obtain expected optical traps. For the same sum of squares due to error SSE and fitting coefficient η, the iterative number from using the improved GS algorithm is smaller than that from using traditional GS algorithm, and the iteration speed is faster about 27%. Multi-particle trapping is first achieved, and dynamic multiple-particle rotation is further demonstrated, in which multiple changing hologram images are obtained continuously through the improved GS algorithm. The manipulation speed is faster than that from using the traditional GS algorithm. The iterative speed can be further improved if the computer capacities are further optimized. Full article

Optogenetics is a versatile toolset for the functional investigation of excitable cells such as neurons and cardiomyocytes in vivo and in vitro. While monochromatic illumination of these cells for either stimulation or inhibition already enables a wide range of studies, the combination of activation and silencing in one setup facilitates new experimental interrogation protocols. In this work, we present a setup for the simultaneous holographic stimulation and inhibition of multiple cells in vitro. The system is based on two fast ferroelectric liquid crystal spatial light modulators with frame rates of up to 1.7 kHz. Thereby, we are able to illuminate up to about 50 single spots with better than cellular resolution and without crosstalk, perfectly suited for refined network analysis schemes. System-inherent aberrations are corrected by applying an iterative optimization scheme based on Zernike polynomials. These are superposed on the same spatial light modulators that display the pattern-generating holograms, hence no further adaptive optical elements are needed for aberration correction. A near-diffraction-limited spatial resolution is achieved over the whole field of view, enabling subcellular optogenetic experiments by just choosing an appropriate microscope objective. The setup can pave the way for a multitude of optogenetic experiments, in particular with cardiomyocytes and neural networks. Full article

The iterative Fourier transform algorithm (IFTA) is widely used in various optical communication applications based on liquid crystal on silicon spatial light modulators. However, the traditional iterative method has many disadvantages, such as a poor effect, an inability to select an optimization direction, and the failure to consider zero padding or phase quantization. Moreover, after years of development, the emergence of various variant algorithms also makes it difficult for researchers to choose one. In this paper, a new intelligent hybrid algorithm that combines the IFTA and differential evolution algorithm is proposed in a novel way. The reliability of the proposed algorithm is verified by beam splitting, and the IFTA and symmetrical IFTA algorithms, for comparison, are introduced. The hybrid algorithm improves the defects above while considering the zero padding and phase quantization of a computer-generated hologram, which optimizes the directional optimization in the diffraction efficiency and the fidelity of the output beam and improves the results of these two algorithms. As a result, the engineers’ trouble in the selection of an algorithm has also been reduced. Full article

Photocurable three-dimensional (3D) printing is a stepwise layer-by-layer fabrication process widely used in the manufacture of highly specialized objects. Current 3D printing techniques are easily implemented; however, the build rate is slow and the surface quality is less than ideal. Holographic 3D display (3DHD) technology makes it possible to reform planar wavefronts into a 3D intensity distribution, which appears as a 3D image in space. This paper examined the application of holographic imaging technology to 3D printing based on photocurable polymers. The proposed system uses a 3DHD diffractive optics system based on a liquid-crystal-on-silicon spatial light modulator (LCoS-SLM), wherein a 3D layered image is created in the optical near field, based on a computer-generated hologram (CGH) optimized using the iterative angular spectrum algorithm (IASA) and a circular IASA. From a single CGH, multiple 2D sliced images are created in space to form a 3D optical image used to initiate the photopolymerization of photocurable resin to form 3D objects. In experiments, the proposed 3D printing system was used to create five polymer objects with a maximum axial length of 25 mm and minimum feature width of 149 μm. The phase-only CGH reformed the incident light into a distribution of optical intensity with high diffraction efficiency suitable for photocuring. Despite limitations pertaining to fabrication area and axial complexity in this initial study, the proposed method demonstrated high light efficiency, high resolution in the lateral direction, rapid fabrication, and good object continuity. Full article

Computer holography is a technology that use a mathematical model of optical holography to generate digital holograms. It has wide and promising applications in various areas, especially holographic display. However, traditional computational algorithms for generation of phase-type holograms based on iterative optimization have a built-in tradeoff between the calculating speed and accuracy, which severely limits the performance of computational holograms in advanced applications. Recently, several deep learning based computational methods for generating holograms have gained more and more attention. In this paper, a convolutional neural network for generation of multi-plane holograms and its training strategy is proposed using a multi-plane iterative angular spectrum algorithm (ASM). The well-trained network indicates an excellent ability to generate phase-only holograms for multi-plane input images and to reconstruct correct images in the corresponding depth plane. Numerical simulations and optical reconstructions show that the accuracy of this method is almost the same with traditional iterative methods but the computational time decreases dramatically. The result images show a high quality through analysis of the image performance indicators, e.g., peak signal-to-noise ratio (PSNR), structural similarity (SSIM) and contrast ratio. Finally, the effectiveness of the proposed method is verified through experimental investigations. Full article

The Gerchberg–Saxton (GS) algorithm is a Fourier iterative algorithm that can effectively optimize phase-only computer-generated holograms (CGHs). This study proposes a new optimization technique for phase-only CGHs based on the gradient descent method. The proposed technique evaluates the intensity distributions of reconstructed images to directly obtain the phase distributions of the CGHs, whereas the GS algorithm equivalently evaluates the amplitude distributions of reconstructed images and extracts phase distributions from complex-amplitude distributions of the holograms using a constant-amplitude constraint. The proposed technique can reduce the errors in the reconstructed images with fewer iterations than the GS algorithm. Full article

A weighted constraint iterative algorithm is presented to calculate phase holograms with quality reconstruction. The image plane is partitioned into two regions where different constraint strategies are implemented during the iteration process. In the image plane, the signal region is constrained directly according to the amplitude distribution of the target image based on an adaptive strategy, whereas the non-signal region is constrained indirectly by total energy control of the hologram plane based on the energy conservation principle. The weighted constraint strategy can improve the reconstruction quality of the phase holograms by broadening the optimizing space of the iterative algorithm, leading to effective convergence of the iteration process. Finally, numerical and optical experiments have been performed to validate the feasibility of our method. Full article

A complex amplitude hologram can reconstruct perfect light waves. However, as there are no spatial light modulators that are able to display complex amplitudes, we need to use amplitude, binary, or phase-only holograms. The images reconstructed from such holograms will deteriorate; to address this problem, iterative hologram optimization algorithms have been proposed. One of the iterative algorithms utilizes a blank area to help converge the optimization; however, the calculation time and memory usage involved increases. In this study, we propose to reduce the computational complexity and memory usage of the iterative optimization using scaled diffraction, which can calculate light propagation with different sampling pitches on a hologram plane and object plane. Scaled diffraction can introduce a virtual blank area without using physical memory. We further propose a combination of scaled diffraction-based optimization and conventional methods. The combination algorithm improves the quality of a reconstructed complex amplitude while accelerating optimization. Full article