Non-diffractive computational ghost imaging

Tailoring nondiffracting fields with a non-Markovian phase imprint

We experimentally generate nondiffracting speckles that carry non-Markovian properties by encoding the wavefront of a monochromatic laser beam with ring-shaped non-Markovian phases. The resulting non-Markovian nondiffracting fields present a ring-shaped pattern and central dark notches, which are analyzed with an expression of the orbital angular momentum spectra of the wavefront possessing ring-shaped non-Markovian phases. Furthermore, we demonstrate that the intensity profiles of these non-Markovian nondiffracting fields exhibit stability over multiple Rayleigh ranges, and their statistical properties could be controlled with the non-Markovianity of the input phase masks. This work presents an approach for simultaneously tailoring the diffracting property and non-Markovianity of optical fields and provides a deeper understanding of non-Markovian processes.

Ghost images with controllable visibility and spatial resolution

We designed a kind of speckle field with controllable visibility and speckle grain size through a modified Gerchberg-Saxton algorithm based on Fresnel diffraction. Ghost images with independently controllable visibility and spatial resolution were demonstrated based on the designed speckle fields, which could be of much higher visibility and spatial resolution than those with pseudothermal light. In addition, speckle fields capable of reconstructing ghost images simultaneously on multiple different planes were customized. These results could be of potential applications on optical encryption and optical tomography.

Tailoring 3D Speckle Statistics

We experimentally generate three-dimensional speckles with customized intensity statistics. By appropriately modulating the phase front of a laser beam, the far-field speckles can maintain a desired intensity probability density function upon axial propagation: while evolving into different spatial patterns. We also demonstrate how to design speckle patterns that obtain distinct tailored intensity statistics on multiple designated axial planes. The ability to design 3D speckle statistics opens many possibilities: three-dimensional imaging and sensing, optical trapping, and manipulation.

Ghost imaging with Bayesian denoising method

We propose a Bayesian denoising method to improve the quality of ghost imaging. The proposed method achieved the highest PSNR and SSIM in both binary and gray-scale targets with fewer measurements. Experimentally, it obtained a reconstructed image of a USAF target where the PSNR and SSIM of the image were up to 12.80 dB and 0.77, respectively, whereas those of traditional ghost images were 7.24 dB and 0.28 with 3000 measurements. Furthermore, it was robust against additive Gaussian noise. Thus, this method could make the ghost imaging technique more feasible as a practical application.

Generation of Non-Rayleigh Nondiffracting Speckles

Optical speckle fields with both non-Rayleigh statistics and nondiffracting characteristics in propagation are an important light source for many applications. However, tailoring either non-Rayleigh statistical speckles or nondiffracting speckles are only investigated independently in previous studies. Here, we report the first observation of optical speckles that remain diffraction-free over a long axial distance while keeping non-Rayleigh statistics simultaneously. We further show the enhancement of Anderson localization of light with the non-Rayleigh nondiffracting speckles. The work presented here provides a versatile framework for customizing optical fields with desired speckle patterns for applications in the fields of solid-state physics, cold atoms, and optical imaging.

Computational ghost imaging with spatiotemporal encoding pseudo-random binary patterns

Computational ghost imaging (CGI) can reconstruct the pixelated image of a target without lenses and image sensors. In almost all spatial CGI systems using various patterns reported in the past, people often only focus on the distribution of patterns in the spatial dimension but ignore the possibility of encoding in the time dimension or even the space-time dimension. Although the random illumination pattern in CGI always brings some inevitable background noise to the recovered image, it has considerable advantages in optical encryption, authentication, and watermarking technologies. In this paper, we focus on stimulating the potential of random lighting patterns in the space-time dimension for embedding large amounts of information. Inspired by binary CGI and second-order correlation operations, we design two novel generation schemes of pseudo-random patterns for information embedding that are suitable for different scenarios. Specifically, we embed a total of 10,000 ghost images (64 × 64 pixels) of the designed Hadamard-matrix-based data container patterns in the framework of CGI, and these ghost images can be quantitatively decoded to two 8-bit standard grayscale images, with a total data volume of 1, 280, 000 bits. Our scheme has good noise resistance and a low symbol error rate. One can design the number of lighting patterns and the information capacity of the design patterns according to the trade-off between accuracy and efficiency. Our scheme, therefore, paves the way for CGI using random lighting patterns to embed large amounts of information and provides new insights into CGI-based encryption, authentication, and watermarking technologies.

Thermal Light Longitudinal Correlated Imaging with Random Orthogonal Matching Pursuit Algorithm

A thermal light correlated longitudinal imaging experiment is proposed. The quasi-thermal light beam is split into two beams, a test beam and a reference beam, respectively. The light in the test beam is scattered by two amplitude objects with a specific longitudinal distance between them, while the light of the reference beam travels uninterrupted. At the end of the test and reference beams, two charge-coupled detectors (CCDs) are used to measure the intensity of the optical field. Through intensity correlation measurement the images of the two detected objects can be achieved simultaneously, only if the distance between the objects is less than the longitudinal coherent length. The theoretical analysis shows that the longitudinal coherent length is determined by both the transverse size of the incoherent thermal light source and the length of the optical path. The quality of the correlated images of the two objects is improved greatly by making use of the orthogonal matching pursuit (OMP) and the proposed variant random orthogonal matching pursuit (Random-OMP) algorithms. The experimental results show that the Random-OMP algorithm is more effective than the OMP algorithm for increasing both the visibility and continuity of the images. The experimental scenario can mimic an optical tomography imaging system, and the two objects with longitudinal distance can be taken as the two transverse layers of a three-dimensional object. The proposed Random-OMP algorithm is effective for improving the quality of the tomography image and has potential value in optical tomography imaging technology using incoherent light sources.

Hyperuniformity in amorphous speckle patterns

Hyperuniform structures possess the ability to confine and drive light, although their fabrication is extremely challenging. Here we demonstrate that speckle patterns obtained by a superposition of randomly arranged sources of Bessel beams can be used to generate hyperunifrom scalar fields. By exploiting laser light tailored with a spatial filter, we experimentally produce (without requiring any computational power) a speckle pattern possessing maxima at locations corresponding to a hyperuniform distribution. By properly filtering out intensity fluctuation from the same speckle pattern, it is possible to retrieve an intensity profile satisfying the hyperuniformity requirements. Our findings are supported by extensive numerical simulations.

High frame-rate computational ghost imaging system using an optical fiber phased array and a low-pixel APD array

To obtain a high imaging frame rate, a computational ghost imaging system scheme is proposed based on optical fiber phased array (OFPA). Through high-speed electro-optic modulators, the randomly modulated OFPA can provide much faster speckle projection, which can be precomputed according to the geometry of the fiber array and the known phases for modulation. Receiving the signal light with a low-pixel APD array can effectively decrease the requirement on sampling quantity and computation complexity owing to the reduced data dimensionality while avoiding the image aliasing due to the spatial periodicity of the speckles. The results of analysis and simulation show that the frame rate of the proposed imaging system can be significantly improved compared with traditional systems.

Adaptive foveated single-pixel imaging with dynamic supersampling

In contrast to conventional multipixel cameras, single-pixel cameras capture images using a single detector that measures the correlations between the scene and a set of patterns. However, these systems typically exhibit low frame rates, because to fully sample a scene in this way requires at least the same number of correlation measurements as the number of pixels in the reconstructed image. To mitigate this, a range of compressive sensing techniques have been developed which use a priori knowledge to reconstruct images from an undersampled measurement set. Here, we take a different approach and adopt a strategy inspired by the foveated vision found in the animal kingdom-a framework that exploits the spatiotemporal redundancy of many dynamic scenes. In our system, a high-resolution foveal region tracks motion within the scene, yet unlike a simple zoom, every frame delivers new spatial information from across the entire field of view. This strategy rapidly records the detail of quickly changing features in the scene while simultaneously accumulating detail of more slowly evolving regions over several consecutive frames. This architecture provides video streams in which both the resolution and exposure time spatially vary and adapt dynamically in response to the evolution of the scene. The degree of local frame rate enhancement is scene-dependent, but here, we demonstrate a factor of 4, thereby helping to mitigate one of the main drawbacks of single-pixel imaging techniques. The methods described here complement existing compressive sensing approaches and may be applied to enhance computational imagers that rely on sequential correlation measurements.