Compressed ghost imaging based on differential speckle patterns

We propose a compressed ghost imaging scheme based on differential speckle patterns,named CGI-DSP.In the scheme,a series of bucket detector signals are acquired when a series of random speckle patterns are employed to illuminate an unknown object.Then the differential speckle patterns(differential bucket detector signals) are obtained by taking the difference between present random speckle patterns(present bucket detector signals) and previous random speckle patterns(previous bucket detector signals).Finally,the image of object can be obtained directly by performing the compressed sensing algorithm on the differential speckle patterns and differential bucket detector signals.The experimental and simulated results reveal that CGI-DSP can improve the imaging quality and reduce the number of measurements comparing with the traditional compressed ghost imaging schemes because our scheme can remove the environmental illuminations efficiently.     

Compressed ghost edge imaging

In this Letter, we propose an advanced framework of ghost edge imaging, named compressed ghost edge imaging(CGEI). In the scheme, a set of structured speckle patterns with pixel shifting illuminate on an unknown object.The output is collected by a bucket detector without any spatial resolution. By using a compressed sensing algorithm, we obtain horizontal and vertical edge information of the unknown object with the bucket detector detection results and the known structured speckle patterns. The edge is finally constructed via twodimensional edge information. The experimental and numerical simulations results show that the proposed scheme has a higher quality and reduces the number of measurements, in comparison with the existing edge detection schemes based on ghost imaging.     

High speed ghost imaging based on a heuristic algorithm and deep learning

We report an overlapping sampling scheme to accelerate computational ghost imaging for imaging moving targets,based on reordering a set of Hadamard modulation matrices by means of a heuristic algorithm. The new condensed overlapped matrices are then designed to shorten and optimize encoding of the overlapped patterns, which are shown to be much superior to the random matrices. In addition, we apply deep learning to image the target, and use the signal acquired by the bucket detector and corresponding real image to train the neural network. Detailed comparisons show that our new method can improve the imaging speed by as much as an order of magnitude, and improve the image quality as well.     

Full color ghost imaging by using both time and code division multiplexing technologies

We propose a new full color ghost imaging scheme using both time and code division multiplexing technologies. In the scheme, the speckle patterns of three colors (red, green and blue) are modulated with different time slots and codes. The light intensity is sampled by one bucket detector. Then based on the modulated time slots and codes, we can effectively and simultaneously extract three detection component signals corresponding to three color components of objects from the sampling signal of the bucket detector. Finally, three component images resulting from the three component detection signals can be synthesized into a full color image. The experimental results verify the feasibility of our scheme under the limit of the number of time slots and codes. Moreover, our scheme reduces the number of bucket detectors and can realize high quality imaging even in a noisy environment.     

Optical encryption scheme based on ghost imaging with disordered speckles

An optical encryption scheme based on a ghost imaging system with disordered speckles is proposed to obtain a higher security with a small key. In the scheme, Alice produces the random speckle patterns and obtains the detection results with the help of a computational ghost imaging(CGI) system. Then Alice permutes the order of the random speckle patterns and shares the permutation sequence as a secure key to the authorized users. With the secure key, Bob could recover the object with the principle of the CGI system, whereas, the unauthorized users could not obtain any information of the object. The numerical simulations and experimental results show that the proposed scheme is feasible with a small key, simultaneously,it has a higher security. When the eavesdropping ratio(ER) is less than 40%, the eavesdropper cannot acquire any useful information. Meanwhile, the authorized users could recover completely with the secure key.     

Orthogonal-triangular decomposition ghost imaging

Ghost imaging (GI) offers great potential with respect to conventional imaging techniques. However, there are still some obstacles for reconstructing images with high quality, especially in the case that the orthogonal measurement matrix is impossible to construct. In this paper, we propose a new scheme based on the orthogonal-triangular (QR) decomposition, named QR decomposition ghost imaging (QRGI) to reconstruct a better image with good quality. In the scheme, we can change the randomly non-orthogonal measurement matrix into orthonormal matrix by performing QR decomposition in two cases. (1) When the random measurement matrix is square, it can be firstly decomposed into an orthogonal matrix $\bm Q$ and an upper triangular matrix $\bm R$. Then let the off-diagonal values of $\bm R$ equal to 0.0, the diagonal elements of $\bm R$ equal to a constant $k$, where $k$ is the average of all values of the main diagonal, so the resulting measurement matrix can be obtained. (2) When the random measurement matrix is with full rank, we firstly compute its transpose, and followed with above QR operation. Finally, the image of the object can be reconstructed by correlating the new measurement matrix and corresponding bucket values. Both experimental and simulation results verify the feasibility of the proposed QRGI scheme. Moreover, the results also show that the proposed QRGI scheme could improve the imaging quality comparing to traditional GI (TGI) and differential GI (DGI). Besides, in comparison with the singular value decomposition ghost imaging (SVDGI), the imaging quality and the reconstruction time by using QRGI are similar to those by using SVDGI, while the computing time (the time consuming on the light patterns computation) is substantially shortened.     

Handwritten digit recognition based on ghost imaging with deep learning

We present a ghost handwritten digit recognition method for the unknown handwritten digits based on ghost imaging(GI) with deep neural network, where a few detection signals from the bucket detector, generated by the cosine transform speckle, are used as the characteristic information and the input of the designed deep neural network(DNN), and the output of the DNN is the classification. The results show that the proposed scheme has a higher recognition accuracy(as high as98% for the simulations, and 91% for the experiments) with a smaller sampling ratio(say 12.76%). With the increase of the sampling ratio, the recognition accuracy is enhanced. Compared with the traditional recognition scheme using the same DNN structure, the proposed scheme has slightly better performance with a lower complexity and non-locality property.The proposed scheme provides a promising way for remote sensing.     

Lensless ghost imaging through the strongly scattering medium

Lensless ghost imaging has attracted much interest in recent years due to its profound physics and potential applications. In this paper we report studies of the robust properties of the lensless ghost imaging system with a pseudo-thermal light source in a strongly scattering medium. The effects of the positions of the strong medium on the ghost imaging are investigated. In the lensless ghost imaging system, a pseudo-thermal light is split into two correlated beams by a beam splitter. One beam goes to a charge-coupled detector camera, labeled as CCD2. The other beam goes to an object and then is collected in another charge-coupled detector camera, labeled as CCD1, which serves as a bucket detector. When the strong medium, a pane of ground glass disk, is placed between the object and CCD1, the bucket detector, the quality of ghost imaging is barely affected and a good image could still be obtained. The quality of the ghost imaging can also be maintained, even when the ground glass is rotating, which is the strongest scattering medium so far. However, when the strongly scattering medium is present in the optical path from the light source to CCD2 or the object, the lensless ghost imaging system hardly retrieves the image of the object. A theoretical analysis in terms of the second-order correlation function is also provided.     

Computational lensless ghost imaging in a slant path non-Kolmogorov turbulent atmosphere

Based on the computational ghost-imaging arrangement with “virtual detector” and the extended Huygens–Fresnel integral, lensless ghost imaging with fully spatially incoherent light radiation through a slant turbulent channel has been studied. The analytical ghost-imaging formulas have been derived. Our formulas shown that the image quality is influenced by the turbulence strength, the propagation distance, the zenith angle of communication channel and the fractal constant of the non-Kolmogorov power spectrum of atmospheric turbulence. In the case of the short-exposure imaging and the bucket detector detection for test field, the influence of the atmospheric turbulence on the quality of the ghost imaging mainly come from the path which is ahead of object.     

Correspondence imaging based on correlation coefficients

In the context of correspondence ghost imaging, we utilize the correlation coefficients to separate the reference detector speckle patterns into positive and negative correlated parts. A positive image and a negative image of the object are obtained by averaging over corresponding speckle patterns. The visibility and contrast-to-noise ratio of the positive image are discussed, and it is found that the latter will reach a maximum by averaging over a little less than half of the total number of reference speckle patterns.     

针对多散斑图的差分压缩鬼成像方案研究

鬼成像方案实现所需设备、成像的质量以及成像所花的时间是决定鬼成像技术可实用化的重要因素. 本文提出一种针对多散斑图的差分压缩鬼成像方案. 该方案通过连续探测多个独立的散斑图, 降低了热光鬼成像方案对探测器高时间分辨力的要求; 通过采用差分方法, 抑制了背景噪声和其他噪声源的干扰; 通过使用压缩感知重建算法, 有效地降低了鬼成像所需时间并同时提升成像的质量. 数值仿真结果表明, 对于二灰度“N” 图, 本方案在8000次的采样情形下与多散斑图鬼成像方案35000次采样的结果相比, 均方误差降低了96.9%、峰值信噪比提升15.1 dB. 对于八灰度“Pepper”图, 本方案与多散斑图鬼成像方案相比, PSNR提升11.4 dB. 本方案可降低探测设备的要求、提高成像质量、降低重建时间, 具有广阔的应用前景.     

基于小波树和哈达玛矩阵的自适应快速三维压缩成像方法

针对光子计数系统实现三维成像速度缓慢的问题,提出一种基于小波树和哈达玛矩阵的自适应快速三维压缩成像方法。利用哈达玛矩阵调制投影图案提高采样效率,被调制的短脉冲结构光照射场景,单像素光子计数探测器采集回波。通过分析低分辨率图像的小波树选择采样区域,使用哈达玛矩阵调制所选采样区域得到的投影图案,可采集图像细节,多阶段采样后利用哈达玛反变换恢复出高分辨率图像。实验结果表明,采集并恢复出一幅512×512像素的三维图像的时间最快可达到41 s。     

Secret shared multiple-image encryption based on row scanning compressive ghost imaging and phase retrieval in the Fresnel domain

A multiple-image encryption method is proposed that is based on row scanning compressive ghost imaging, (t, n) threshold secret sharing, and phase retrieval in the Fresnel domain. In the encryption process, after wavelet transform and Arnold transform of the target image, the ciphertext matrix can be first detected using a bucket detector. Based on a (t, n) threshold secret sharing algorithm, the measurement key used in the row scanning compressive ghost imaging can be decomposed and shared into two pairs of sub-keys, which are then reconstructed using two phase-only mask (POM) keys with fixed pixel values, placed in the input plane and transform plane 2 of the phase retrieval scheme, respectively; and the other POM key in the transform plane 1 can be generated and updated by the iterative encoding of each plaintext image. In each iteration, the target image acts as the input amplitude constraint in the input plane. During decryption, each plaintext image possessing all the correct keys can be successfully decrypted by measurement key regeneration, compression algorithm reconstruction, inverse wavelet transformation, and Fresnel transformation. Theoretical analysis and numerical simulations both verify the feasibility of the proposed method.     

Color ghost imaging via sparsity constraint and non-local self-similarity

We propose a color ghost imaging approach where the object is illuminated by three-color non-orthogonal random patterns. The object’s reflection/transmission information is received by only one single-pixel detector, and both the sparsity constraint and non-local self-similarity of the object are utilized in the image reconstruction process. Numerical simulation results demonstrate that the imaging quality can be obviously enhanced by ghost imaging via sparsity constraint and nonlocal self-similarity(GISCNL), compared with the reconstruction methods where only the object’s sparsity is used. Factors affecting the quality of GISCNL, such as the measurement number and the detection signal-to-noise ratio, are also studied.     

日光强度涨落自关联消湍流成像

从关联成像理论出发,提出了日光场在实际大气湍流环境中强度点对点自关联成像理论,并进行了实验验证,分析了太阳光强度二阶自关联成像和强度点对点二阶自关联成像的区别.研究结果表明,太阳光场的点对点四阶自关联,即强度的二阶点对点自关联,可实现消大气湍流成像.为验证理论有效性,利用外场实验进行了验证,获得优于17 km距离的消湍流成像结果.理论和实验均表明,太阳光强度涨落的点对点自关联可实现消大气湍流成像.相比于相机直接成像,本文成像方法消除了大气湍流影响,同时该方案极大提升了关联成像技术的实用性,可直接用于远距离消大气湍流的高质量成像,增加图像识别率.理论表明,任何成像过程中波前受相位扰动影响的波段,如红外、紫外等,均可利用本文方法消除影响,成果具有较大实用价值.     

基于Hadamard矩阵优化排序的快速单像素成像

为提升单像素成像速度,提出了基于Hadamard矩阵优化排序的压缩采样解决方案.利用数值仿真和室外实验对提出的5种排序方法进行了对比分析.研究结果表明:按Haar小波变换系数绝对值排序时单像素成像效果最优,排序对应到Walsh序后可利用快速变换重建图像,速度达300帧/秒@64×64像素;最优排序下,采样率25%仍可重建图像,采样速度可提升4倍.针对排序方法与成像信噪比关系,从关联成像角度给出了其物理解释:测量基矩阵元邻域数值相等的区域面积等效于光场二阶相干面积,当光场二阶相干面积随测量基由大到小排序时成像效果最优.本文研究成果可用于提升单像素成像速度,具有实用价值.     

实验研究探测器大小与散焦长度对无透镜鬼衍射的影响

无透镜鬼衍射是一种特殊的非局域关联成像技术,通过对包含物体信息的测试光路和不含物体信息的参考光路的光场强度涨落关联进行测量,在参考光路上可得到物体的衍射图样。利用赝热光源实验研究了探测器尺寸大小和光路散焦长度对无透镜鬼衍射质量的影响。实验以四缝物体为例,定量研究了探测器大小和散焦是如何改变无透镜鬼衍射的成像结果,并和理论模拟进行了比较,获得了比较一致的结果。利用图像相关度定量分析了实验结果与理想无透镜鬼衍射图像的差别,发现这两者都会使无透镜鬼衍射的质量变差。     

Ghost imaging-based optical cryptosystem for multiple images using integral property of the Fourier transform

A novel ghost imaging-based optical cryptosystem for multiple images using the integral property of the Fourier transform is proposed. Different from other multiple-image encryption schemes, we mainly construct the modulation patterns related to the plaintext images to realize the encrypted transmission of multiple images. In encryption process, the first image is encrypted by the ghost imaging encryption scheme, and the intensity sequence obtained by the bucket detector is used as the ciphertext. Then modulation patterns of other images are constructed by using the integral property of the Fourier transform and used as the keys. Finally, the ciphertext and keys are transmitted to the receiver to complete the encryption process. During decryption, the receiver uses different keys to decrypt the ciphertext and gets different plaintext images, and decrypted images have no image aliasing problem. Experiments and simulations verify the feasibility, security, and robustness of the proposed scheme. This scheme has high scalability and broad application prospect, which provides a new idea for optical information encryption.     

Optimization of speckle patterns in ghost imaging via sparse constraints by mutual coherence minimization

In this Letter the problem of optimization of speckle patterns in a ghost imaging(GI) system is addressed. The mutual coherence between the measuring matrix and the sparsifying dictionary matrix is minimized to obtain the required speckle patterns. Simulation and experimental results are presented, both showing that the quality of the reconstructed results obtained with the optimized speckle patterns is much improved in comparison with that obtained with the general unoptimized ones. We expect this method can be used to design GI systems with high performance.     

Ghost imaging based on Pearson correlation coefficients

Correspondence imaging is a new modality of ghost imaging, which can retrieve a positive/negative image by simple conditional averaging of the reference frames that correspond to relatively large/small values of the total intensity measured at the bucket detector. Here we propose and experimentally demonstrate a more rigorous and general approach in which a ghost image is retrieved by calculating a Pearson correlation coefficient between the bucket detector intensity and the brightness at a given pixel of the reference frames, and at the next pixel, and so on. Furthermore, we theoretically provide a statistical interpretation of these two imaging phenomena, and explain how the error depends on the sample size and what kind of distribution the error obeys. According to our analysis, the image signal-to-noise ratio can be greatly improved and the sampling number reduced by means of our new method.