End-to-end compression-aware computer-generated holography.

Joint photographic experts group (JPEG) compression standard is widely adopted for digital images. However, as JPEG encoding is not designed for holograms, applying it typically leads to severe distortions in holographic projections. In this work, we overcome this problem by taking into account the influence of JPEG compression on hologram generation in an end-to-end fashion. To this end, we introduce a novel approach to merge the process of hologram generation and JPEG compression with one differentiable model, enabling joint optimization via efficient first-order solvers. Our JPEG-aware end-to-end optimized holograms show significant improvements compared to conventional holograms compressed using JPEG standard both in simulation and on experimental display prototype. Specifically, the proposed algorithm shows improvements of 4 dB in peak signal-to-noise ratio (PSNR) and 0.27 in structural similarity (SSIM) metrics, under the same compression rate. When maintained with the same reconstruction quality, our method reduces the size of compressed holograms by about 35% compared to conventional JPEG-compressed holograms. Consistent with simulations, the experimental results further demonstrate that our method is robust to JPEG compression loss. Moreover, our method generates holograms compatible with the JPEG standard, making it friendly to a wide range of commercial software and edge devices.

Polarized deep diffractive neural network for sorting, generation, multiplexing, and de-multiplexing of orbital angular momentum modes.

The multiplexing and de-multiplexing of orbital angular momentum (OAM) beams are critical issues in optical communication. Optical diffractive neural networks have been introduced to perform sorting, generation, multiplexing, and de-multiplexing of OAM beams. However, conventional diffractive neural networks cannot handle OAM modes with a varying spatial distribution of polarization directions. Herein, we propose a polarized optical deep diffractive neural network that is designed based on the concept of dielectric rectangular micro-structure meta-material. Our proposed polarized optical diffractive neural network is optimized to sort, generate, multiplex, and de-multiplex polarized OAM beams. The simulation results show that our network framework can successfully sort 14 kinds of orthogonally polarized vortex beams and de-multiplex the hybrid OAM beams into Gauss beams at two, three, and four spatial positions, respectively. Six polarized OAM beams with identical total intensity and eight cylinder vector beams with different topology charges have also been sorted effectively. Additionally, results reveal that the network can generate hybrid OAM beams with high quality and multiplex two polarized linear beams into eight kinds of cylinder vector beams.

Image steganography with visual illusion.

Human eyes are often "cheated" by an optical illusion (or visual illusion) so that the perceived image differs from the physical reality. But various optical illusions have been seldom investigated for technological applications such as image processing and optical display in the past. As a unique attempt of combining information technology with optical illusion, we propose a novel image steganography scheme based on a color assimilation illusion. A synthesized image containing a grayscale background and a saturated color line (or point) grid can be perceived as a color image, with external secret data hidden simultaneously.

Phase-only color rainbow holographic near-eye display.

Color rainbow holography can realize color holographic 3D display without speckle noise under white light illumination. However, traditional color rainbow holograms used for high-resolution static color 3D display or near-eye color display are amplitude-type, resulting in low diffraction efficiency due to the presence of conjugate light. In this Letter, a phase-only color rainbow holographic near-eye display is demonstrated. The calculation of a phase-only color rainbow hologram is realized by combining a band-limited diffraction and a bi-directional error diffusion algorithm with high-frequency blazed gratings coded to control longitudinal dispersion. When the wavelength of illumination light is deviated from the designated wavelength of the hologram, only a certain wavefront aberration is caused, but there is no conjugate light. The phase-only color rainbow holographic near-eye display of both a 2D color image and a 3D scene are implemented by optical experiments. It has potential applications in head-mounted 3D augmented reality displays without vergence-accommodation conflict.

Does deep learning always outperform simple linear regression in optical imaging?

Deep learning has been extensively applied in many optical imaging problems in recent years. Despite the success, the limitations and drawbacks of deep learning in optical imaging have been seldom investigated. In this work, we show that conventional linear-regression-based methods can outperform the previously proposed deep learning approaches for two black-box optical imaging problems in some extent. Deep learning demonstrates its weakness especially when the number of training samples is small. The advantages and disadvantages of linear-regression-based methods and deep learning are analyzed and compared. Since many optical systems are essentially linear, a deep learning network containing many nonlinearity functions sometimes may not be the most suitable option.

Known-plaintext attack to optical encryption systems with space and polarization encoding.

Space-based optical encryption (SBOE) and double random polarization encoding (DRPO) are previously considered to be more secure than common random-phase-encoding-based optical cryptosystems. The known-plaintext attack (KPA) to SBOE and DRPO was seldomly investigated in the past. A matrix regression approach based on training samples is proposed in this paper to crack these two optical cryptosystems. The relationship between plaintexts and ciphertexts is directly modeled by a complex-amplitude weighting matrix, which is optimized by a gradient descent algorithm. This approach has a simple model compared with deep learning and the KPA can be implemented without recovering the exact key. Our proposed KPA schemes reveal the security flaws of SBOE and DRPO, as well as other linear optical cryptosystems.

Visual cryptography in single-pixel imaging.

Two novel visual cryptography (VC) schemes are proposed by combining VC with single-pixel imaging (SPI) for the first time. It is pointed out that the overlapping of visual key images in VC is similar to the superposition of pixel intensities by a single-pixel detector in SPI. In the first scheme, QR-code VC is designed by using opaque sheets instead of transparent sheets. The secret image can be recovered when identical illumination patterns are projected onto multiple visual key images and a single detector is used to record the total light intensities. In the second scheme, the secret image is shared by multiple illumination pattern sequences and it can be recovered when the visual key patterns are projected onto identical items. The application of VC can be extended to more diversified scenarios by our proposed schemes.

Motion estimation and quality enhancement for a single image in dynamic single-pixel imaging.

In single-pixel imaging (SPI), a large number of illuminations is usually required to capture one single image. Consequently, SPI may only achieve a very low frame rate for a fast-moving object and the reconstructed images are contaminated with blur and noise. In previous works, some attempts are made to perform motion estimation between neighboring frames in a SPI video to enhance the image quality. However, the motion estimation and quality enhancement from one single image frame in dynamic SPI was seldom investigated. In this work, it assumed that some prior knowledge about the type of motion the object undergoes is known. A motion model of the target object is constructed and the motion parameters can be optimized within a search space. Our proposed scheme is different from common motion deblur techniques for photographs since the motion blur mechanism in SPI is significantly different from a conventional camera. Experimental results demonstrate that the reconstructed images with our proposed scheme in dynamic SPI have much better quality.

Optical machine learning with incoherent light and a single-pixel detector.

An optical diffractive neural network (DNN) can be implemented with a cascaded phase mask architecture. Like an optical computer, the system can perform machine learning tasks such as number digit recognition in an all-optical manner. However, the system can work only under coherent light illumination, and the precision requirement in practical experiments is quite high. This Letter proposes an optical machine learning framework based on single-pixel imaging (MLSPI). The MLSPI system can perform the same linear pattern recognition task as DNN. Furthermore, it can work under incoherent lighting conditions, has lower experimental complexity, and can be easily programmable.

Error diffusion method with optimized weighting coefficients for binary hologram generation.

The error diffusion method can effectively reduce quality degradation by propagating thresholding errors to neighboring pixels in the conversion of a gray-scale hologram to a binary hologram. In previous works, the four weighting coefficients in error diffusion are mostly set as the Floyd-Steinberg coefficient, which was determined empirically and originally proposed for photograph processing. In this work, we point out that the Floyd-Steinberg coefficients can be suboptimal for hologram error diffusion binarization. Furthermore, the weighting coefficients are optimized for each different hologram adaptively. Compared with conventional coefficients, our optimized coefficients can better preserve the fidelity of a reconstructed image after a hologram is binarized.

Secured single-pixel broadcast imaging.

Active single-pixel imaging (also known as illumination-modulated single-pixel imaging) employs a spatial light modulator to illuminate a scene with structured patterns. The scheme of active single-pixel imaging is similar to a wireless broadcast system, allowing that multiple receivers use a single-pixel detector to capture an image simultaneously from a different place. The use of basis patterns allows for high-quality reconstructions and an efficient sampling process, but the public knowledge of the basis patterns is not a favorable feature for security applications. In order to develop a secured broadcast single-pixel imaging system, we propose to employ block-permutated Hadamard basis patterns for illumination. The randomness in permutation operations introduces strong security characteristics for the system. Both simulation and experimental results demonstrate our proposed scheme has satisfactory imaging quality and efficiency. This work generates a new insight for the application of single-pixel imaging and provides a solution for developing a secured imaging system for non-visible wavebands.

Special ciphertext-only attack to double random phase encryption by plaintext shifting with speckle correlation.

In this paper, a special ciphertext-only attack (COA) scenario to the traditional double random phase encoding (DRPE) technique is proposed based on plaintext shifting. We assume the attacker can illegally manipulate the DRPE system to gain multiple ciphertexts from randomly shifted versions of the same plaintext. The plaintext image can be recovered when our proposed scenario is combined with a speckle correlation attacking method proposed in previous work. Simulation results demonstrate that our proposed scheme can successfully crack the DRPE system even when the speckle correlation method alone fails to work in the conventional single ciphertext scenario due to the small size of the plaintext image. The work in this paper reveals a severe security flaw of DRPE systems when minor position shifting of the plaintext occurs.

Is QR code an optimal data container in optical encryption systems from an error-correction coding perspective?

Quick response (QR) code has been employed as a data carrier for optical cryptosystems in many recent research works, and the error-correction coding mechanism allows the decrypted result to be noise free. However, in this paper, we point out for the first time that the Reed-Solomon coding algorithm in QR code is not a very suitable option for the nonlocally distributed speckle noise in optical cryptosystems from an information coding perspective. The average channel capacity is proposed to measure the data storage capacity and noise-resistant capability of different encoding schemes. We design an alternative 2D barcode scheme based on Bose-Chaudhuri-Hocquenghem (BCH) coding, which demonstrates substantially better average channel capacity than QR code in numerical simulated optical cryptosystems.

Fast computer generated hologram calculation with a mini look-up table incorporated with radial symmetric interpolation.

The amount of heavy computation in Computer Generated Hologram (CGH) can be significantly reduced by pre-computing look-up tables. However, the huge memory usage of look-up tables is a major challenge. To address this problem, the Look-up tables can be efficiently compressed by methods such as radial symmetric interpolation. In this paper, we notice that there is still data redundancy in the look-up table of radial symmetric interpolation method and the table size can be further compressed to 5%-10% or even less of original, by our proposed mini look-up table approach based on Principal Component Analysis (PCA). The compressed look-up table in our scheme only occupies a memory size of around 200-300 KB or even less. Moreover, the proposed scheme will introduce almost no extra cost of computation speed slowdown and reconstructed image quality degradation, compared to conventional method.

High-resolution parallel phase-shifting digital holography using a low-resolution phase-shifting array device based on image inpainting.

Parallel phase-shifting digital holography can record high-quality holograms efficiently from fast-moving objects in a dynamic scene. However, a phase-shifting array device with a cell size identical to image sensors is required, which imposes difficulty in practice. This Letter proposes a novel scheme to employ a low-resolution phase-shifting array device to achieve high-resolution parallel phase-shifting digital holography, based on image inpainting performed on incomplete holograms. The experimental results validate the effectiveness of the proposed scheme.