Single-pixel Imaging Technique Research Articles

Single pixel quantitative phase imaging with spatial frequency projections.

We introduce a new single pixel imaging technique that automatically co-registers quantitative phase and incoherent image modalities through the simultaneous acquisition of identical object spatial frequency information. The technique consists of using a time varying groove density diffraction grating to produce a reference and scan beam. The interference between the beams produce time varying spatial frequencies in the sample. The collected light on a single pixel detector produces a time trace that allows easy recovery of coherent and incoherent contrast mechanisms. We derive theory for the quantitative phase and show excellent agreement with experimental data and numeric model. Additionally, we derive a general theory of single pixel quantitative phase theory that can be applied broadly to general methods that use a sequence of modulated light patterns for single pixel phase imaging.

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.

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.

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.

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.

Theoretical analysis of spectrum reconstruction imaging using single-pixel detection

As a novel imaging method, single-pixel imaging based on spectrum reconstruction is interesting. To date, however, there has not yet been a theory that can analyze the method in detail. In order to obtain a comprehensive understanding of the single-pixel imaging technique, a detailed theoretical analysis is proposed. Firstly, in the presented imaging theory, we analyze the effects of several factors involved in the imaging process on imaging reconstruction, including the direct detection, namely, the back scattering light from the imaged object is received by a detector; indirect detection, namely, the back scattering light is received after undergoing the diffuse reflections by multiple diffusing surfaces in proper sequence; multi-channel detection, namely, the scattering light is together detected after experiencing multiple diffuse reflections in proper sequence along multiple different paths; the size and location of the single-pixel detector. The theoretical results show that whether it is direct detection or indirect detection and whether it is single-channel detection or multi-channel detection, the above imaging method is valid as long as the scattering light can be received by the detector, and the obtained results are also in accord with the existing experimental results. Since the single-pixel detector is treated as a component of many point detectors due to its practical size, the effect of the single-pixel detector size on image reconstruction is equivalent to the integration of reconstructed images from multiple point detectors at different locations. Secondly, the spectrum reconstruction based on a three-step phase shift technique is also derived to increase the image reconstruction speed. Finally, the experimental results of the imaging reconstruction of an object, whose surface reflectivity is uniform, are demonstrated.

Three-dimensional single-pixel imaging with far fewer measurements than effective image pixels.

Typical single-pixel imaging techniques inherently consume a large number of measurements to reconstruct a high-quality and high-resolution image. Three-dimensional (3-D) single-pixel imaging with both high sampling efficiency and high depth accuracy remains a challenge. We implement fringe projection virtually by exploiting Helmholtz reciprocity. Depth information is modulated into a deformed fringe pattern whose Fourier spectrum is sampled by using sinusoidal intensity pattern illumination and single-pixel detection. The fringe pattern has a highly focused first-order component in its Fourier spectrum, which allows us to efficiently acquire the depth information from measurements far fewer than illumination pattern pixels. The 3-D information is retrieved through Fourier analysis. We experimentally obtained a 3-D reconstruction of a complex object with 599×599 effective pixels, achieving a measurement-to-pixel ratio of 5.78%. The depth accuracy is evaluated at sub-millimetric level by using a test object.

Single-pixel remote imaging based on Walsh-Hadamard transform

Single-pixel imaging has become a topic of intense interest amongst theoreticians and experimentalists in recent years, and is still attracting great attention due to its potential applications in biomedical imaging, remote sensing, defence monitoring, etc. Two main fields should be involved in single-pixel imaging scheme: single-pixel camera and computational quantum imaging, which are proposed in the year 2006 and 2008, respectively. Although these two single-pixel imaging schemes belong to different research fields, they are nearly identical in the realization setup and using the similar image recovering algorithm. The single-pixel camera scheme is mainly based on compressive sensing algorithms, which can recover the image with about 30 percent measurements of its total pixels (raster scan method), but need the prior knowledge of the image. While the computational quantum imaging method usually recovers the image by using the second-order correlation function, which is computational fast but need more measurements to retrieve a high quality image. Thus, both the methods mentioned above are time consuming. In this paper, a single-pixel imaging scheme based on Walsh-Hadamard transform is proposed and is demonstrated both theoretically and experimentally. The retrieving times of different algorithms are discussed and compared with each other. An image of 10241024 pixels can be acquired around 1 second with our method while it will take 8 seconds by using TVAL3 algorithm on the general computer in our numerical simulation experiment. It is also experimentally demonstrated that the nature targets from 500 meters to 5000 meters away are acquired, with pixels of 128128 and in the waveband of 350-900 nm, and the speed of the imaging frame rate is achieved at 0.5 frame per second. The differences and commons between single-pixel imaging and computational quantum imaging are also discussed in this article. It is found that the Walsh-Hadamard transform we proposed is stable and can be sufficiently saving the imaging time of the single-pixel imaging schemes while maintaining a high imaging quality. Moreover, the single-pixel remote imaging scheme can be used in other wave band such as infrared and micro wave imaging, or will be useful in the case when the array detector technique is difficult to meet the requirements such as the sensitivity or the volume. And our scheme proposed here can make the single-pixel imaging technique step further toward its real applications.

Guided compressive sensing single-pixel imaging technique based on hierarchical model

Single-pixel imaging has emerged a decade ago as an imaging technique that exploits the theory of compressive sensing. In this research, the problem of optimizing the measurement matrix in compressive sensing framework was addressed. Thus far, random measurement matrices are widely used because they provide small coherence. However, recent reports claim that measurement matrix can be optimized, thereby improving its performance. Based on such proposition, this study proposed an alternative approach of optimizing the measurement matrix in a hierarchical model. In particular, this study constructed the hierarchical model based on an increasing resolution grade by exploiting the guided information and the adaptive step size method. An image with a demanded resolution was then obtained using the l1-norm method. Subsequently, the performance of the introduced method was verified and compared with those of existing approaches via several experiments. Results of the tests indicated that the reconstruction quality of optimizing the measurement matrix was improved when the proposed method was used.

Single-pixel imaging by means of Fourier spectrum acquisition.

Single-pixel imaging techniques enable to capture a scene without a direct line of sight to the object, but high-quality imaging has been proven challenging especially in the presence of noisy environmental illumination. Here we present a single-pixel imaging technique that can achieve high-quality images by acquiring their Fourier spectrum. We use phase-shifting sinusoid structured illumination for the spectrum acquisition. Applying inverse Fourier transform to the obtained spectrum yields the desired image. The proposed technique is capable of capturing a scene without a direct view of it. Thus, it enables a feasible placement of detectors, only if the detectors can collect the light signals from the scene. The technique is also a compressive sampling like approach, so it can reconstruct an image from sub-Nyquist measurements. We experimentally obtain clear images by utilizing a detector not placed in direct view of the imaged scene even with noise introduced by environmental illuminations.

Single-pixel infrared and visible microscope

Microscopy is an essential tool in a huge range of research areas. Until now, microscopy has been largely restricted to imaging in the visible region of the electromagnetic spectrum. Here we present a microscope system that uses single-pixel imaging techniques to produce images simultaneously in the visible and shortwave infrared. We apply our microscope to the inspection of various objects, including a silicon CMOS sensor, highlighting the complementarity of the visible and shortwave infrared wavebands. The system is capable of producing images with resolutions between 32×32 and 128×128 pixels at corresponding frame rates between 10 and 0.6 Hz. We introduce a compressive technique that does not require postprocessing, resulting in a predicted frame rate increase by a factor 8 from a compressive ratio of 12.5% with only 28% relative error.

Spatially-chirped modulation imaging of absorbtion and fluorescent objects on single-element optical detector

Line imaging of fluorescent and absorptive objects with a single-pixel imaging technique that acquires one-dimensional cross-sections through a sample by imposing a spatially-varying amplitude modulation on the probing beam is demonstrated. The fluorophore concentration or absorber distribution of the sample is directly mapped to modulation frequency components of the spatially-integrated temporal signal. Time-domain signals are obtained from a single photodiode, with object spatial frequency correlation encoded in time-domain bursts in the electronic signal from the photodiode.