Single-pixel Imaging System Research Articles

A performance metric for screen selection with the acoustic single pixel imager.

In the recent literature, an Acoustic Single-Pixel Imager has been successfully developed for source localization in a two-dimensional waveguide. Source bearing angle estimation was carried out by applying sparse recovery techniques on sensor measurements taken over different imaging screens. This paper shows that the Mutual Coherence of the sensing matrix can be used as a metric to predict the source localization capability of the single-pixel imaging system. In particular, this paper's analysis focuses on the sparsity of open cells within the imaging screen and the number of imaging screens used to maximize the probability of correct detection over varying levels of source sparsity. In this work, a simulation environment to demonstrate how the mutual coherence of the sensing matrix correlates with source localization performance over source sparsity, sparsity of open screen cells, and number of measurements used for sparse recovery is developed. The analysis shows that the leading factor in source localization performance gains is primarily from the number of imaging screens used to measure the acoustic wave-field.

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.

Suppressing the noise in binarized Fourier single-pixel imaging utilizing defocus blur

Sinusoidal Fourier patterns are one of the orthogonal basis patterns used in single-pixel imaging. By retrieving the complex Fourier coefficients with phase-shifting algorithm, it reconstructs the image of a scene using inverse Fourier transform. It has been shown that Fourier single-pixel imaging is particularly well-suited to non-conventional imaging applications. However, the frame rate of Fourier single-pixel imaging system is limited because the Fourier patterns are grayscale while the digital micromirror device performs binary modulation much faster than grayscale modulation. The fast Fourier single-pixel imaging addressed the problem by binarizing the patterns, however, the quality of the reconstructed image is jeopardized by the extra induced noise. Here we proposed to suppress the binarization induced noise while keeping the high-speed merit by deliberately applying a precomputed defocus. Numerical simulation and experimental results showed that the proposed method reconstructed images with an averaged 12% lower root mean squared error and ∼90% higher signal-to-noise ratio than the fast Fourier method did. To some extent, the proposed method overcame the limitation of the quality-speed trade-off in Fourier single-pixel imaging and made both low noise and high frame rate available simultaneously.

Enhancing the image resolution in a single-pixel sub-THz imaging system based on compressed sensing

Compressed sensing (CS) techniques allow for faster imaging when combined with scan architectures, which typically suffer from speed. This technique when implemented with a subterahertz (sub-THz) single detector scan imaging system provides images whose resolution is only limited by the pixel size of the pattern used to scan the image plane. To overcome this limitation, the image of the target can be oversampled; however, this results in slower imaging rates especially if this is done in two-dimensional across the image plane. We show that by implementing a one-dimensional (1-D) scan of the image plane, a modified approach to CS theory applied with an appropriate reconstruction algorithm allows for successful reconstruction of the reflected oversampled image of a target placed in standoff configuration from the source. The experiments are done in reflection mode configuration where the operating frequency is 93 GHz and the corresponding wavelength is λ = 3.2 mm. To reconstruct the image with fewer samples, CS theory is applied using masks where the pixel size is 5 mm × 5 mm, and each mask covers an image area of 5 cm × 5 cm, meaning that the basic image is resolved as 10 × 10 pixels. To enhance the resolution, the information between two consecutive pixels is used, and oversampling along 1-D coupled with a modification of the masks in CS theory allowed for oversampled images to be reconstructed rapidly in 20 × 20 and 40 × 40 pixel formats. These are then compared using two different reconstruction algorithms, TVAL3 and l1-MAGIC. The performance of these methods is compared for both simulated signals and real signals. It is found that the modified CS theory approach coupled with the TVAL3 reconstruction process, even when scanning along only 1-D, allows for rapid precise reconstruction of the oversampled target.

Edge detection based on single-pixel imaging.

In the paper, we propose a new edge detection schemes, based on a single-pixel imaging in the frequency domain. In SCHEME-I, special sinusoidal patterns for the x-direction edge and also y-direction edge of the unknown object are first designed. The frequency spectrum for the edge is then obtained using the a four-step phase-shifting technique with the designed sinusoidal patterns in a single-pixel imaging system. In SCHEME-II, the frequency spectrum of the unknown object is first obtained, then the frequency spectrum for the edge is obtained by calculations. The resulting edges are finally obtained by the inverse Fourier transform on their frequency spectrum. We have also verified the proposed schemes by experiments and numerical simulations. The results show that the proposed schemes can produce higher quality edges of character and also image objects. Comparing with SCHEME-II, the application of SCHEME-I to high frequency components has greatly improved signal-to-noise ratio of the received data in the bucket detector, resulting in better experimental results. Comparing with the edge detection scheme by speckle-shifting in ghost imaging systems, the proposed SCHEME-I shows an improvement in the signal-to-noise ratio. Since a single-pixel imaging system is used, the proposed schemes are capable of reconstructing edges from indirect measurements. The number of measurements required can be effectively reduced due to the sparsity of natural images in the Fourier domain and the conjugate symmetry of real-valued signals' Fourier spectrum.

Detecting the Trajectory of Moving Object for Single-Pixel Imaging System

In order to get the trajectory of moving object using single-pixel imaging system, an algorithm is proposed. The same pseudorandom masks are employed to illuminate the different time scene. A time weighted sum of the background correction signals is employed to get the trajectory information using compressed sensing (CS) method. In ideal situation, we can obtain other parameters (e.g., speed, orientation) besides the trajectory. However, the reflective intensity of the object can be change due to the reflective angle change caused by the motion in some situations. This will mislead for achieving the speed, orientation parameters. In order to eliminate this effect, a division method is utilized. At last, the computer simulation results prove the effect validity of the proposed algorithm.

How do plants see the world? - UV imaging with a TiO2 nanowire array by artificial photosynthesis.

The concept of plant vision refers to the fact that plants are receptive to their visual environment, although the mechanism involved is quite distinct from the human visual system. The mechanism in plants is not well understood and has yet to be fully investigated. In this work, we have exploited the properties of TiO2 nanowires as a UV sensor to simulate the phenomenon of photosynthesis in order to come one step closer to understanding how plants see the world. To the best of our knowledge, this study is the first approach to emulate and depict plant vision. We have emulated the visual map perceived by plants with a single-pixel imaging system combined with a mechanical scanner. The image acquisition has been demonstrated for several electrolyte environments, in both transmissive and reflective configurations, in order to explore the different conditions in which plants perceive light.

Image reconstruction of dynamic infrared single-pixel imaging system

Single-pixel imaging technique has recently received much attention. Most of the current single-pixel imaging is aimed at relatively static targets or the imaging system is fixed, which is limited by the number of measurements received through the single detector. In this paper, we proposed a novel dynamic compressive imaging method to solve the imaging problem, where exists imaging system motion behavior, for the infrared (IR) rosette scanning system. The relationship between adjacent target images and scene is analyzed under different system movement scenarios. These relationships are used to build dynamic compressive imaging models. Simulation results demonstrate that the proposed method can improve the reconstruction quality of IR image and enhance the contrast between the target and the background in the presence of system movement.

Image Retrieval in Spatial and Temporal Domains With a Quadrant Detector

To retrieve an N pixel image of a scene, conventional digital cameras record the information using an N pixelated detector with one measurement, while single-pixel imaging achieves it by sampling the image in a particular basis and recording the light intensities of N temporal measurements with a single-pixel detector. Besides these two schemes, it is also possible to obtain the same spatial information with an X pixels detector and N / X measurements, where the pressure of information retrieval is distributed to both spatial and temporal domains, rather than condensed in one domain. In this paper, we investigate this possibility and present a 4-pixels imaging scheme, which retrieves an image partially in spatial domain and partially in temporal domain, by adopting a quadrant detector to a single-pixel imaging system. While yielding images with equal quality, the proof-of-principle system we built is four times faster than a standard single-pixel imaging system, demonstrating the feasibility of the proposed scheme. Our work exploits the flexibility of space-time information retrieval and can be useful for applications where comprise between spatial and temporal domains is needed.

Principles and applications of high-speed single-pixel imaging technology

Single-pixel imaging (SPI) technology has garnered great interest within the last decade because of its ability to record high-resolution images using a single-pixel detector. It has been applied to diverse fields, such as magnetic resonance imaging (MRI), aerospace remote sensing, terahertz photography, and hyperspectral imaging. Compared with conventional silicon-based cameras, single-pixel cameras (SPCs) can achieve image compression and operate over a much broader spectral range. However, the imaging speed of SPCs is governed by the response time of digital micromirror devices (DMDs) and the amount of compression of acquired images, leading to low (ms-level) temporal resolution. Consequently, it is particularly challenging for SPCs to investigate fast dynamic phenomena, which is required commonly in microscopy. Recently, a unique approach based on photonic time stretch (PTS) to achieve high-speed SPI has been reported. It achieves a frame rate far beyond that can be reached with conventional SPCs. In this paper, we first introduce the principles and applications of the PTS technique. Then the basic architecture of the high-speed SPI system is presented, and an imaging flow cytometer with high speed and high throughput is demonstrated experimentally. Finally, the limitations and potential applications of high-speed SPI are discussed.

Collective noise model for focal plane modulated single-pixel imaging

Single-pixel imaging, also known as computational ghost imaging, provides an alternative method to perform imaging in various applications which are difficult for conventional cameras with pixelated detectors, such as multi-wavelength imaging, three-dimensional imaging, and imaging through turbulence. In recent years, many improvements have successfully increased the signal-to-noise ratio of single-pixel imaging systems, showing promise for the engineering feasibility of this technique. However, many of these improvements are based on empirical findings. In this work we perform an investigation of the noise from each system component that affects the quality of the reconstructed image in a single-pixel imaging system based on focal plane modulation. A collective noise model is built to describe the resultant influence of these different noise sources, and numerical simulations are performed to quantify the effect. Experiments have been conducted to verify the model, and the results agree well with the simulations. This work provides a simple yet accurate method for evaluating the performance of a single-pixel imaging system, without having to carry out actual experimental tests.

Super Resolution Imaging Based on a Dynamic Single Pixel Camera

In this paper, we present a super resolution imaging method based on a dynamic single pixel camera. First, the proposed method obtains subhigh-resolution (HR) images with subpixel shifts by the dynamic single pixel camera. To achieve this purpose, the patterns on the digital micromirror device are subpixel shifted instead of mechanical scanning. Then, the final HR image can be reconstructed by sub-HR images and wiener filter. In order to avoid the subpixel shifts error that caused by the instability of the system, a subpixel registration algorithm is adopted. Besides, to improve the signal-noise-ratio (SNR) performance of the measurements, a simple and effective method based on the correlation of the signal and the randomness of the noise is adopted. Compared with traditional single pixel imaging system, the proposed method has a remarkable performance at spatial resolution and SNR. The feasibility of the proposed method is demonstrated by simulations and experiments.

Performance assessment of a compressive sensing single-pixel imaging system

Conventional sensors measure the light incident at each pixel in a focal plane array. Compressive sensing (CS) involves capturing a smaller number of unconventional measurements from the scene, and then using a companion process to recover the image. CS has the potential to acquire imagery with equivalent information content to a large format array while using smaller, cheaper, and lower bandwidth components. However, the benefits of CS do not come without compromise. The CS architecture chosen must effectively balance between physical considerations, reconstruction accuracy, and reconstruction speed to meet operational requirements. Performance modeling of CS imagers is challenging due to the complexity and nonlinearity of the system and reconstruction algorithm. To properly assess the value of such systems, it is necessary to fully characterize the image quality, including artifacts and sensitivity to noise. Imagery of a two-handheld object target set was collected using an shortwave infrared single-pixel CS camera for various ranges and number of processed measurements. Human perception experiments were performed to determine the identification performance within the trade space. The performance of the nonlinear CS camera was modeled by mapping the nonlinear degradations to an equivalent linear shift invariant model. Finally, the limitations of CS modeling techniques are discussed.

Analysis of detection bandwidth limitations in time-stretch-based single-pixel imaging systems

Single-pixel imaging (SPI) has recently attracted considerable attention in magnetic resonance imaging and remote sensing for its data compression capability and broad operational wavelength range. However, the frame rates of single-pixel cameras are largely limited by the response time of digital micromirror devices (DMDs). To circumvent this challenge, a novel SPI technique called time-stretch-based single-pixel imaging (TSSPI) is proposed, which can increase the imaging speed of single-pixel cameras based on DMD by over 3 orders of magnitude. In the TSSPI system, photodetection bandwidth and pulse repetition rate are critical parameters influencing the quality of reconstructed images. In this paper, we quantitatively analyze their effects on reconstruction accuracy through simulation and experiment for the first time. Photodetectors with various bandwidths are separately used to acquire the same number of measurements for image reconstruction and the peak signal-to-noise ratios of the reconstructed images are calculated to evaluate the reconstruction accuracy. We experimentally demonstrate that the ratio between photodetection bandwidth and pulse repetition rate has a strong impact on reconstruction quality. A threshold for this ratio is estimated and high-quality image reconstruction can be achieved only above this threshold. In our experiment, a 400-MHz detection bandwidth is demonstrated to be an optimized parameter set which can balance the trade-off between the system cost and the reconstruction accuracy with respect to a 50-MHz pulse repetition rate. In addition, we also demonstrate that the ratio is related to the complexity of the illuminated scene.

Nonconvex compressive video sensing.

High-speed cameras explore more details than normal cameras in the time sequence, while the conventional video sampling suffers from the trade-off between temporal and spatial resolutions due to the sensor's physical limitation. Compressive sensing overcomes this obstacle by combining the sampling and compression procedures together. A single-pixel-based real-time video acquisition is proposed to record dynamic scenes, and a fast nonconvex algorithm for the nonconvex sorted ℓ1 regularization is applied to reconstruct frame differences using few numbers of measurements. Then, an edge-detection-based denoising method is employed to reduce the error in the frame difference image. The experimental results show that the proposed algorithm together with the single-pixel imaging system makes compressive video cameras available.

Evaluation of the impact of diffraction on image reconstruction in single-pixel imaging systems.

In single-pixel coded aperture terahertz-imaging, the individual pixel size in the spatial terahertz modulator is usually comparable to the terahertz wavelength in order to obtain a sufficient spatial image resolution. Therefore, diffraction plays an important role in the imaging process and must be accurately taken into account when the image is computationally retrieved. For this reason, we analyzed the impact of diffraction from the spatial terahertz modulator on the quality of the reconstructed image in single-pixel coded aperture imaging. We observed that the most important fraction of the image information is already contained in the zero order diffracted radiation. Higher diffraction orders do not contain enough information to retrieve the image from them solely, yet can contribute to an improved image quality when added to the zero order information.

Extended-field coverage hyperspectral camera based on a single-pixel technique.

A spectral single-pixel imaging system facilitates effective image compression, but the imaging region is limited by its single detector. This paper presents a hyperspectral camera that allows extended-field coverage to be collected by one detector. Compressive data of a large field of view is achieved by our highly sensitive detection camera, which can be extended to near-infrared or infrared spectral monitoring. We acquire a hyperspectral datacube of 256×256 spatial pixels and 3 nm spectral resolution at a sampling rate of 25%. Finally, we apply our camera to monitoring fruit freshness nondestructively by differentiating a banana's ripeness over time.

Single-pixel camera with one graphene photodetector.

Consumer cameras in the megapixel range are ubiquitous, but the improvement of them is hindered by the poor performance and high cost of traditional photodetectors. Graphene, a two-dimensional micro-/nano-material, recently has exhibited exceptional properties as a sensing element in a photodetector over traditional materials. However, it is difficult to fabricate a large-scale array of graphene photodetectors to replace the traditional photodetector array. To take full advantage of the unique characteristics of the graphene photodetector, in this study we integrated a graphene photodetector in a single-pixel camera based on compressive sensing. To begin with, we introduced a method called laser scribing for fabrication the graphene. It produces the graphene components in arbitrary patterns more quickly without photoresist contamination as do traditional methods. Next, we proposed a system for calibrating the optoelectrical properties of micro/nano photodetectors based on a digital micromirror device (DMD), which changes the light intensity by controlling the number of individual micromirrors positioned at + 12°. The calibration sensitivity is driven by the sum of all micromirrors of the DMD and can be as high as 10(-5)A/W. Finally, the single-pixel camera integrated with one graphene photodetector was used to recover a static image to demonstrate the feasibility of the single-pixel imaging system with the graphene photodetector. A high-resolution image can be recovered with the camera at a sampling rate much less than Nyquist rate. The study was the first demonstration for ever record of a macroscopic camera with a graphene photodetector. The camera has the potential for high-speed and high-resolution imaging at much less cost than traditional megapixel cameras.

一种双层散射介质中间目标单像素成像系统研究

一种双层散射介质中间目标单像素成像系统研究

Imaging through dynamic scattering media with compressed sensing

Imaging through scattering media has been a focus in research because of its meaningful applications in many fields. Recently, it has been proposed that high quality images can be recovered after passing through stationary scattering media by using the single-pixel imaging system based on compressed sensing. No doubt, it is a very interesting discovery about compressed sensing. However, it is also reported that high quality image can be recovered only with stationary scattering media. Mostly, the scattering media will not remain stationary, for example, the properties of the fog will be dynamically changed when their is wind. Thus, in a dynamic case, the transmittance of the scattering media will be nonlinear over the time, which will make the measured data nonlinear and the reconstructed image quality decrease. In this paper, a novel algorithm of linear transformation for measured data (LTMD) is proposed to make the nonlinear attenuation factor gain a linear transformation after passing through the dynamic scattering media. The factor is proposed from the theoretical calculus based on compressed sensing, and this correction factor can help to eliminate the nonlinear errors caused by dynamic scattering media and make the measured data linear. So the transformed data will greatly upgrade the reconstructed image quality. Simulation results show that high peak singnal to noise ratio images can still be recovered even when the dynamic frequency reaches 300 times in the 900 times of sampling. In experiments, plastic films are used as scattering media, and the number of films can be changed during the sampling to simulate the dynamic state of scattering media. With LTMD, high quality image with a resolution of 64 48 is recovered after passing through dynamic plastic films while the recovered result without LTMD is still hard to be distinguished. The traditional reconstructed algorithms orthogonal matching pursuit, Tval3 and L1-magic are also used in the experiments, and the image is still hard to recover with any of the three traditional algorithms. In a word, the proposed LTMD algorithm uses the correction factor to make the affected nonlinear-measured data linear, so as to increase the reconstructed quality of the imaging system based on the compressed sensing even when passing through scattering media with highly dynamic frequency.