Single-pixel Imaging Scheme Research Articles

Efficient single-pixel imaging based on a compact fiber laser array and untrained neural network

This paper presents an efficient scheme for single-pixel imaging (SPI) utilizing a phase-controlled fiber laser array and an untrained deep neural network. The fiber lasers are arranged in a compact hexagonal structure and coherently combined to generate illuminating light fields. Through the utilization of high-speed electro-optic modulators in each individual fiber laser module, the randomly modulated fiber laser array enables rapid speckle projection onto the object of interest. Furthermore, the untrained deep neural network is incorporated into the image reconstructing process to enhance the quality of the reconstructed images. Through simulations and experiments, we validate the feasibility of the proposed method and successfully achieve high-quality SPI utilizing the coherent fiber laser array at a sampling ratio of 1.6%. Given its potential for high emitting power and rapid modulation, the SPI scheme based on the fiber laser array holds promise for broad applications in remote sensing and other applicable fields.Graphical

Single-pixel imaging based on metasurface fuzzycoding.

Single-pixel imaging, renowned for its high sensitivity, robustness against interference, and superior resolution, has become increasingly prominent in the field of optical research. Over recent years, a diverse array of light modulation devices and methodologies has been devised to accomplish megahertz modulations rates. This work presents a single-pixel imaging scheme based on the fuzzy coding of metasurfaces. This unique encoding technique manipulates the quality of the mask pattern by adjusting the pixel count within the metasurface units. Notably, we expand the metasurface units to effectively mitigate the position sensitivity during movement or rotations, thus easing the challenge for the detector in collecting the correct light intensity during sub-mask transitions. A detailed analysis is drawn of the reconstruction quality of fuzzy masks. Simultaneously, we provide simulations of single-pixel imaging under the condition where the fuzzy-coded metasurface is moving. This work provides a new, to the best of our knowledge, mask generation mode for high-speed spatial light modulation.

Online Denoising Single-Pixel Imaging Using Filtered Patterns

Noise is inevitable in single-pixel imaging (SPI). Although post-processing algorithms can significantly improve image quality, they introduce additional processing time. To address this issue, we propose an online denoising single-pixel imaging scheme at the sampling stage, which uses the filter to optimize the illumination modulation patterns. The image is retrieved through the second-order correlation between the modulation patterns and the intensities detected by the single-pixel detector. Through simulations and experiments, we analyzed the impact of sampling rate, noise intensity, and filter template on the reconstructed images of both binary and grayscale objects. The results demonstrate that the denoising effect is comparable to the imaging-first followed by post-filtering procedures, but the post-processing time is reduced for the same image quality. This method offers a new way for rapid denoising in SPI, and it should be particularly advantageous in applications where time-saving is of paramount importance, such as in image-free large target classification.

Ultrafast single-pixel imaging with high axial resolution by comprehensive utilization of the time-frequency-phase information of a mode-locked laser

An ultrafast single-pixel imaging scheme is proposed to improve the resolution in the vertical direction. A whole row of horizontal and vertical information for a reflecting sample is encoded onto the time, frequency and phase of a space-dispersed ultrafast mode-locked beam. The single-shot spectrum is decoded to reconstruct three-dimensional (3D) imaging by comprehensively extracting the time-frequency-phase information of the interference spectrum from a mode-locked pulse. In the proposed method, the free spectral range (FSR) and phase information are extracted based on Fourier forward and inverse transform from the temporal interferogram. With the help of comprehensive utilization of time-frequency-phase information and time-stretch technique, the imaging system with axial resolution higher than 100 nm, depth measurement range greater than 7.5 mm and 50 MHz line-scan frame rate are experimentally demonstrated.

Chromatic-Aberration-Corrected Hyperspectral Single-Pixel Imaging

With the emerging development of hyperspectral single-pixel imaging (SPI) systems, the trade-off between the simplicity of optical structure and the correction of chromatic aberration is now an essential factor to be considered. To address both issues simultaneously, we propose a chromatic-aberration-corrected hyperspectral single-pixel imaging scheme, which is based on spectral measurement and dispersion correction. Its achromatism feature is evaluated by optical simulations and proof-of-concept experiments. Moreover, to overcome the shortcomings of traditional algorithms, a new adaptive iterative algorithm is employed, which can further optimize image quality. The results demonstrate that both dispersion and noise in our system are significantly reduced. Taking the position coordinate variance as a figure of merit, we have realized an order of magnitude improvement in the lateral chromatic aberration over the spectral range of 400–780 nm compared to that in conventional hyperspectral SPI. Meanwhile, the contrast-to-noise ratio in our system is enhanced on average by 3 dB. To the best of our knowledge, this is the first such demonstration, and the technique presents possibilities for future integrated applications of high spatial/spectral resolution over the entire visible range, and the system has the potential to be scaled down for future integrated applications.

Efficient large-scale single-pixel imaging.

The speed of single-pixel imaging (SPI) is tied to its resolution, which is positively related to the number of modulation times. Therefore, efficient large-scale SPI is a serious challenge that impedes its wide applications. In this work, we report a novel, to the best of our knowledge, sparse SPI scheme and corresponding reconstruction algorithm to image target scenes at above 1 K resolution with reduced measurements. Specifically, we first analyze the statistical importance ranking of Fourier coefficients for natural images. Then the sparse sampling with a polynomially decending probability of the ranking is performed to cover a larger range of the Fourier spectrum than non-sparse sampling. The optimal sampling strategy with suitable sparsity is summarized for the best performance. Next, a lightweight deep distribution optimization (D2O) algorithm is introduced for large-scale SPI reconstruction from sparsely sampled measurements instead of a conventional inverse Fourier transform (IFT). The D2O algorithm empowers robustly recovering sharp scenes at 1 K resolution within 2 s. A series of experiments demonstrate the technique's superior accuracy and efficiency.

Fourier transform profilometry using single-pixel detection based on two-dimensional discrete cosine transform

We present a single-pixel Fourier transform profilometry (FTP) for obtaining three-dimensional (3D) maps with few measurements. Two digital micromirror devices were employed to generate a two-dimensional (2D) sinusoidal illumination pattern and a series of specified sampling patterns, respectively, coupled with a single-pixel detector to sequentially collect spatially light field from an object surface. The reflectance image at the object surface was recovered with single-pixel imaging (SPI) scheme, 3D map of the object surface was reconstructed with FTP from the recovered reflectance image. We incorporated the 2D discrete cosine transform into the SPI scheme to reduce the number of sampling patterns, where only a few sampling patterns whose spatial frequencies around the illumination frequency were required for the measurement. We experimentally reconstructed acceptable 3D maps, the ratios of the number of measurements to the number of pixels of 3D maps were determined to be 1.04% and 1.79% for the 3D reconstructions of simple and complex objects, respectively. This significantly reduces the number of measurements that is necessary for the current 3D reconstruction based on SPI scheme.

Anti-motion blur single-pixel imaging with calibrated radon spectrum.

Single-pixel imaging (SPI), a novel computational imaging technique that has emerged in the past decades, can effectively capture the image of a static object by consecutively measuring light intensities from it. However, when SPI is applied to imaging the dynamic object, severe motion blur in the restored image tends to appear. In this Letter, a new SPI scheme is proposed to largely alleviate such a problem by leveraging a calibrated radon spectrum. Such a spectrum is obtained by translating the acquired one-dimensional projection functions (1DPFs) according to the positional relationship among the 1DPFs. Simulation and experimental results demonstrate that, without prior knowledge, our approach can effectively reduce motion blur and restore high-quality images of the fast-moving object. In addition, the proposed scheme can also be used for fast object tracking.

A Single-Pixel Imaging Scheme with Obstacle Detection

Single-pixel imaging (SPI) utilizes a second-order correlation of structured illumination light field and a single-pixel detector to form images. As the single-pixel detector provides no spatial resolution, a structured illumination light field generated by devices such as a spatial light modulator substitutes the role of array camera to retrieve pixel-wise spatial information. Due to its unique imaging modality, SPI has certain advantages. Meanwhile, its counterintuitive configuration and reciprocity relation to traditional array cameras have been studied to understand its fundamental principle. According to previous studies, the non-spatial detection property makes it possible for SPI to resist scattering in the detection part. In this work, we study the influence of an obstacle aperture in the detection part of SPI. We notice that such an obstacle aperture can restrict the field-of-view (FOV) of SPI, which can be diminished by a scattering process. We investigate these properties with experiment results and analysis under geometry optics. We believe that our study will be helpful in understanding the counterintuitive configuration of SPI and its reciprocity to traditional imaging.

Complex-amplitude single-pixel imaging using coherent structured illumination

This research presents a coherent structured illumination single-pixel imaging scheme to image objects with complex amplitudes. By utilizing a phase-only spatial light modulator for phase modulation, we can efficiently generate the Hadamard basis structured light and the reference light that interfere with each other to form the coherent structured illumination. Using the 4-step phase-shifting, the spectrum of the object is acquired by detecting the zero-frequency component of the object light with a single-pixel photodetector. The desired complex-amplitude image can be further retrieved by applying an inverse Hadamard transform. The proposed scheme is experimentally demonstrated by imaging two etched glass objects, a dragonfly wing, and a resolution test chart. Benefiting from the phase modulation, this scheme has a high efficiency, a high imaging quality, a high spatial resolution, and a simple and stable configuration to obtain both the phase and amplitude information of the target object. The proposed scheme provides a promising complex-amplitude imaging modality with single-pixel detection. Thus it might find broad applications in optical metrology and biomedical science.

Full-color photon-counting single-pixel imaging

We propose and experimentally demonstrate a high-efficiency single-pixel imaging (SPI) scheme by integrating time-correlated single-photon counting (TCSPC) with time-division multiplexing to acquire full-color images at an extremely low light level. This SPI scheme uses a digital micromirror device to modulate a sequence of laser pulses with preset delays to achieve three-color structured illumination, then employs a photomultiplier tube into the TCSPC module to achieve photon-counting detection. By exploiting the time-resolved capabilities of TCSPC, we demodulate the spectrum-image-encoded signals, and then reconstruct high-quality full-color images in a single round of measurement. Based on this scheme, strategies such as single-step measurement, high-speed projection, and undersampling can further improve imaging efficiency.

Single-pixel camera based on a spinning mask.

Single-pixel imaging (SPI) has been intensively studied in recent years for its capacity to obtain 2D images using a non-pixelated detector. However, the traditional modulation modality using an iteratively refreshed spatial light modulator has significantly restricted its imaging speed, which is a primary barrier to its widespread application. In this work, we propose and demonstrate a new, to the best of our knowledge, SPI scheme using a spinning mask for modulation. An annular binary mask is designed and spun to perform fast spatial modulation, neglecting the iterative modulation modality that limits SPI speed. A multi-spectral SPI system at 100 frames per second is demonstrated, covering a wide range of spectra, from ultraviolet to short-wave infrared light. We believe that this elegant and low-cost scheme will enable SPI to pave its way for practical application.

Single-pixel imaging for dynamic targets via a non-diffracting beam

We develop a novel kind of single-pixel imaging (SPI) scheme to reconstruct high-quality images of the axially fast-moving target by utilizing the non-diffracting beam illumination. In this paper, a kind of cosine shaped source is elaborately designed and introduced for the first time in the SPI scheme to realize the reconstruction of the dynamic target. The imaging formula for the SPI system with the cosine shaped source is theoretically derived and numerical examples are given to see clearly the influences of system parameters and motion models of the target on the image quality. Our results show that the image quality and imaging efficiency of the SPI system for the static or dynamic target can be significantly improved by utilizing the cosine shaped source, due to its non-diffracting and orthogonal features. Even there exists strong scattering media, our SPI proposal can still work well for the static or dynamic target. Therefore, our work offers great promise for the SPI real application in forward-looking lidar detection.

Imaging high-speed moving targets with a single-pixel detector.

Single-pixel imaging (SPI) has recently been intensively studied as an alternative to the traditional focal plane array (FPA) technology. However, limited by the refresh rate of spatial light modulators (SLM) and inherent reconstruction mechanism, SPI is inappropriate for high-speed moving targets. To break through this limitation, we propose a novel SPI scheme for high-speed moving targets. In our scenario, the spatial encoding for the target is done by the movement of the target relative to a static pseudo-random illumination pattern. In this process, a series of single-pixel signals are generated that corresponds to the overlap between the target and certain parts of the illumination structure. This correspondence can be utilized for image reconstruction in the same way as normal SPI. In addition, compressive sensing and deep learning algorithms are used for reconstruction, respectively. Reasonable reconstructions can be obtained with a sampling ratio of only 6%. Experimental verification together with theoretical analysis has shown that our scheme is able to image high-speed moving targets that could be alternatively achieved by a fast FPA camera. Our scheme keeps the inherent advantages of SPI and meanwhile extend its application to moving targets. It is believed that this technology will have wide application in many situations.

Fast single-pixel imaging based on optimized reordering Hadamard basis

Single-pixel imaging is a computational imaging scheme that offers novel solutions for multi-spectral imaging, feature-based imaging, polarimetric imaging, three-dimensional imaging, holographic imaging, and optical encryption. The single-pixel imaging scheme can be used for imaging in wave band such as infrared and micro wave imaging, or will be useful in the case where the array detector technique is difficult to meet the requirement such as the sensitivity or the volume. The main limitation for its application comes from a trade-off between spatial resolution and acquisition time, in other words, from relatively high measurement and reconstruction time. Although compressive sensing technique can be used to improve the acquisition time by reducing the number of samplings, the computational time to reconstruct an image is not fast enough to satisfy the real-time video. In this paper, we propose to reduce the required signal acquisition time by using a novel sampling scheme based on optimized ordering of the Hadamard basis, and improve the image reconstruction efficiency by using fast Walsh-Hadamard transform. In our method, the Hadamard basis is rearranged in the ascendant order of the values of its " sparsity” coefficients which are obtained through " Daubechies wavelets 1 (Haar wavelets)”, " Daubechies wavelets 2” wavelet transform and discrete cosine transform, and then compute each total sum of the transformed coefficients’ absolute value, respectively. The measurement order of the Hadamard basis is then rearranged directly according to Walsh order and random permutation order. The peak signal-to-noise ratio (PSNR) and structural similarity index (SSIM) of the retrieved images are computed and compared to test all the five reordering schemes above both in our numerical simulation and outdoor experiments. We find that the reordering method based on Haar wavelet transform is the best PSNR and SSIM and it can reconstruct image under a sampling ratio of 25% which corresponds to the recovering time in which 300 frame per second @64 × 64 pixels single-pixel imaging can be achieved. The optimized measurement order of Hadamard basis greatly simplifies post processing, resulting in significantly faster image reconstruction, which steps further toward high frame rate single-pixel imaging’s applications. Moreover, we propose a novel method to optimize measurement basis in single-pixel imaging, which may be useful in other basis optimizing, such as optimized random speckles, etc.

Single-pixel phase and fluorescence microscope.

Multimodal microscopes either use multiple cameras or a single camera to multiplex different modes spatially. The former needs expertise demanding alignment and the latter suffers from limited spatial resolution. Here, we report an alignment-free full-resolution simultaneous fluorescence and phase imaging approach using single-pixel detectors. By combining reference-free interferometry with single-pixel imaging scheme, we employ structured illumination to encode the phase and fluorescence of the sample into two single-pixel detection arms, and then conduct reconstruction computationally from the illumination patterns and recorded correlated measurements. The recovered fluorescence and phase images are inherently aligned thanks to single-pixel imaging scheme. To validate the proposed method, we built a proof-of-concept setup for first imaging the phase of an etched glass with given etching depth and then imaging the phase and fluorescence of the quantum dot sample. This method holds great potential for multispectral fluorescence microscopy with additional single-pixel detectors or a spectrometer. Besides, this cost-efficient multimodal system might find broad applications in biomedical science and material science.

Single-Pixel Color Imaging Method with a Compressive Sensing Measurement Matrix

Compressive sensing theory has addressed the limitations of traditional methods in the field of information technology, and led to a revolution. On the basis of compressive sensing theory research, this study utilized the exterior determinacy and inherent randomness of chaotic sequences, designed a pseudo-random circulant measurement matrix based on chaotic sequence. Compared with other deterministic measurement matrices, the restoration effect of the designed measurement matrix remarkably improved and showed advantages in hardware and storage. Then, this study developed a single-pixel imaging scheme that could accurately obtain color information. The proposed improved measurement matrix combined with the hardware system could accurately reconstruct color images and had good robustness according to various experimental data.

Photon-counting-based diffraction phase microscopy combined with single-pixel imaging

We propose a photon-counting (PC)-based quantitative-phase imaging (QPI) method for use in diffraction phase microscopy (DPM) that is combined with a single-pixel imaging (SPI) scheme (PC-SPI-DPM). This combination of DPM with the SPI scheme overcomes a low optical throughput problem that has occasionally prevented us from obtaining quantitative-phase images in DPM through use of a high-sensitivity single-channel photodetector such as a photomultiplier tube (PMT). The introduction of a PMT allowed us to perform PC with ease and thus solved a dynamic range problem that was inherent to SPI. As a proof-of-principle experiment, we performed a comparison study of analogue-based SPI-DPM and PC-SPI-DPM for a 125-nm-thick indium tin oxide (ITO) layer coated on a silica glass substrate. We discuss the basic performance of the method and potential future modifications of the proposed system.

Hadamard single-pixel imaging versus Fourier single-pixel imaging.

Single-pixel imaging which employs active illumination to acquire spatial information is an innovative imaging scheme and has received increasing attentions in recent years. It is applicable to imaging at non-visible wavelengths and imaging under low light conditions. However, single-pixel imaging has once encountered problems of low reconstruction quality and long data-acquisition time. Hadamard single-pixel imaging (HSI) and Fourier single-pixel imaging (FSI) are two representative deterministic model based techniques. Both techniques are able to achieve high-quality and efficient imaging, remarkably improving the applicability of single-pixel imaging scheme. In this paper, we compare the performances of HSI and FSI with theoretical analysis and experiments. The results show that FSI is more efficient than HSI while HSI is more noise-robust than FSI. Our work may provide a guideline for researchers to choose suitable single-pixel imaging technique for their applications.

Improving the signal-to-noise ratio of single-pixel imaging using digital microscanning.

Single-pixel cameras provide a means to perform imaging at wavelengths where pixelated detector arrays are expensive or limited. The image is reconstructed from measurements of the correlation between the scene and a series of masks. Although there has been much research in the field in recent years, the fact that the signal-to-noise ratio (SNR) scales poorly with increasing resolution has been one of the main limitations prohibiting the uptake of such systems. Microscanning is a technique that provides a final higher resolution image by combining multiple images of a lower resolution. Each of these low resolution images is subject to a sub-pixel sized lateral displacement. In this work we apply a digital microscanning approach to an infrared single-pixel camera. Our approach requires no additional hardware, but is achieved simply by using a modified set of masks. Compared to the conventional Hadamard based single-pixel imaging scheme, our proposed framework improves the SNR of reconstructed images by ∼ 50 % for the same acquisition time. In addition, this strategy also provides access to a stream of low-resolution 'preview' images throughout each high-resolution acquisition.