Incoherent digital holographic spectral imaging with high accuracy of image pixel registration

Fresnel incoherent correlation holography(FINCH) is a unique three-dimensional(3D) imaging technique which has the advantages of scanning-free,high resolution,and easy matching with existing mature optical systems.In this article,an incoherent digital holographic spectral imaging method with high accuracy of spectral reconstruction based on liquid crystal tunable filter(LCTF) and FINCH is proposed.Using the programmable characteristics of spatial light modulator(SLM),a series of phase masks,none of whose focal lengths changes with wavelength,is designed and made.For each wavelength of LCTF output,SLM calls three phase masks with different phase constants at the corresponding wavelength,and CCD records three holograms.The spectral images obtained by this method have a constant magnification,which can achieve pixel-level image registration,restrain image registration errors,and improve spectral reconstruction accuracy.The results show that this method can not only obtain the 3D spatial information and spectral information of the object simultaneously,but also have high accuracy of spectral reconstruction and excellent color reproducibility.

Method for eliminating zero-order image in digital holography

For eliminating the zero-order image in digital holography, a new method using the differential of the hologram intensity instead of the hologram itself for numerical reconstruction is proposed. This method is based on digital image processing. By analyzing the spatial spectrum of the off-axis digital hologram, it theoretically proves that the zero-order image can be effectively eliminated by differential before reconstruction. Then, the detected hologram is processed in the program with differential and reconstruction. Both the theoretical analysis and digital reconstruction results show that it can effectively eliminate the large bright spot in the center of the reconstructed image caused by the zero-order image, improve the image quality significantly, and render a better contrast of the reconstructed image. This method is very simple and convenient due to no superfluous optical elements and requiring only one time record.

Optical Image Encryption Based on Mixed Chaotic Maps and Single-Shot Digital Holography

Random phase masks play a key role in optical image encryption schemes based on double random phase technique. In this paper, a mixed chaotic method is proposed, which can efficiently solve some weaknesses that one-dimensional (1-D) single chaotic maps encounter to generate random phase masks. Based on the chaotic random phase masks, optical image encryption and decryption are realized with a single-shot digital holographic technique. In the proposed encryption scheme, the initial value and parameters of mixed chaotic maps serve as secret keys, which is convenient for the key management and transmission. Moreover, it also possesses high resistance against statistical attack, brute-force attack, noise attack and shear attack. Simulation results and security analysis verify the validity and security of the proposed encryption scheme. © 2017, Tianjin University and Springer-Verlag Berlin Heidelberg.

Deep learning assisted variational Hilbert quantitative phase imaging

We propose a high-accuracy artifacts-free single-frame digital holographic phase demodulation scheme for relatively lowcarrier frequency holograms-deep learning assisted variational Hilbert quantitative phase imaging(DL-VHQPI).The method,incorporating a conventional deep neural network into a complete physical model utilizing the idea of residual compensation,reliably and robustly recovers the quantitative phase information of the test objects.It can significantly alleviate spectrum-overlapping-caused phase artifacts under the slightly off-axis digital holographic system.Compared to the conventional end-to-end networks(without a physical model),the proposed method can reduce the dataset size dramatically while maintaining the imaging quality and model generalization.The DL-VHQPI is quantitatively studied by numerical simulation.The live-cell experiment is designed to demonstrate the method's practicality in biological research.The proposed idea of the deep learning-assisted physical model might be extended to diverse computational imaging techniques.

Elimination of the Background Noise of the Decoded Image in Fresnel Zone Plate Scanning Holography

A method of digitally high pass filtering in frequency domain is proposed to eliminate the background noise of the decoded image in Fresnel zone plate scanning holography. The high pass filter is designed as a circular stop, which should be suitable to suppressing the background noise significantly and remain much low frequency information of the object. The principle of high pass filtering is that the Fourier transform of the decoded image is multiplied with the high pass filter. Thus the frequency spectrum of the decoded image without the background noise is achieved. By inverse Fourier transform of the spectrum of the decoded image after multiplying operation, the decoded image without the background noise is obtained. Both of the computer simulations and the experimental results show that the contrast and the signal-to-noise ratio of the decoded image are significantly improved with digital filtering.

Portable lensless wide-field microscopy imaging platform based on digital inline holography and multi-frame pixel super-resolution

In this paper,an irregular displacement-based lensless wide-field microscopy imaging platform is presented by combining digital in-line holography and computational pixel super-resolution using multi-frame processing.The samples are illuminated by a nearly coherent illumination system,where the hologram shadows are projected into a complementary metal-oxide semiconductor-based imaging sensor.To increase the resolution,a multi-frame pixel resolution approach is employed to produce a single holographic image from multiple frame observations of the scene,with small planar displacements.Displacements are resolved by a hybrid approach:(i)alignment of the LR images by a fast feature-based registration method,and(ii)fine adjustment of the sub-pixel information using a continuous optimization approach designed to find the global optimum solution.Numerical method for phase-retrieval is applied to decode the signal and reconstruct the morphological details of the analyzed sample.The presented approach was evaluated with various biological samples including sperm and platelets,whose dimensions are in the order of a few microns.The obtained results demonstrate a spatial resolution of 1.55 μm on a field-of-view of<30 mm^(2).

Perfect digital holographic imaging with high resolutionusing a submillimeter-dimension CCD sensor

In order to improve the resolution of digital holography with a common-dimension charge-coupled device (CCD) sensor, the point spread functions are briefly derived for the commonly used and practical post-magnification, pre-magnification, and image-plane digital holographic microscopic systems. The ultimate resolutions of these systems are analyzed and compared. The results show that the ultimate lateral resolution of pre-magnification digital holography is superior to that of post-magnification digital holography in the same conditions. We also demonstrate that the ultimate lateral resolution of image-plane digital holography has no correlation with the photosensitive dimension of the CCD sensor, and it is not significantly related to the pixel size of the sensor. Moreover, both the ultimate resolution and the imaging quality of image-plane digital holography are superior to that of pre- and post-magnification digital holographic microscopy. High-resolution imaging, whose resolution is close to the ultimate resolution of the microscope objective, can be achieved by image-plane digital holography even with a submillimeter-dimension sensor. This system, by which perfect imaging can be achieved, is optimal for commonly used digital holographic microscopy. Experimental results demonstrate the correctness of the theoretical analysis.

Aperture synthesis based solely on phase images in digital holography

Aperture synthesis is an important approach to improve the lateral resolution of digital holography(DH) techniques.The limitation of the accuracy of registration positions between sub-holograms affects the quality of the synthesized image and even causes the failure of aperture synthesis.It is a major issue in aperture synthesis of DH.Currently intensity images are utilized to find the registration positions of sub-holograms in aperture synthesis.To improve the accuracy of registration positions, we proposed a method based on similarity calculations of the phase images between sub-holograms instead of intensity images.Furthermore, a quantitative indicator, degree of image distortion, was applied to evaluate the synthetic results.Experiments are performed and the results verify that the proposed phase-image-based method is better than the state-of-the-art intensity-image-based techniques in the estimation of registration positions and provides a better synthesized final three-dimensional shape image.

基于数字全息的模糊图像复原技术研究

采用数字全息方法研究物体经散射介质(毛玻璃)成像复原机理。首先,在菲涅尔离轴数字全息原理的基础上,建立了数字全息记录与再现的数学模型。然后,设计和搭建了全息散射成像系统,建立了毛玻璃的数学模型,并提出一种消除毛玻璃散斑噪声的算法,利用菲涅耳再现算法对实验得到的数字全息图进行再现。最后,用频谱滤波法对全息图再处理后进行再现。实验结果验证了理论算法和实验方法的正确性,为今后物体经过复杂介质的图像复原的深入研究提供了帮助。

并行相移同轴数字全息偏振成像方法

为了研究并行相移同轴数字全息系统中偏振态传输的问题,提出考虑偏振的并行相移同轴数字全息系统的修正模型,并依据此模型提出偏振成像方法。首先,介绍了理想情况下并行相移同轴数字全息的原理,然后,介绍了考虑偏振的并行相移同轴数字全息修正模型,最后,基于此模型提出了实现偏振成像的方法。实验结果验证了模型的可行性,通过这种方法可以得到外表信息,成像分辨率可达到14μm。该方法扩充了数字全息系统的功能,通过该系统可以对物体的偏振态进行成像。

红外光透水雾全息成像研究

本文提出一种在水雾环境下进行全息成像的方法。该方法采用波长处于“大气窗口”的红外激光器,通过实验模拟出雾气环境,以探究不同雾气浓度对红外光的全息成像效果影响,并设置可见光数字全息实验作为对比。通过对比红外光与可见光重建图像的不同图像质量评估参数,结果表明该系统红外光可清晰成像,而可见光数字全息系统则成像效果不佳。此外,由于红外光透水雾全息重建像受零级与散斑影响严重,本文对得到的全息图重建像进行消零级与增强Lee滤波去噪声处理,以达到改善图像质量的目的。

数字全息与定量相位成像:进展与展望(特邀)

全息术的提出为光波场的定量分析提供了一个开创性的技术方案。经过70余年的发展,基于全息术的计算成像已成为光场定量测量的重要工具,它的出现为物理学、生物学和材料科学领域提供了新的观测维度,搭建了光学成像和光散射领域的桥梁,突破了传统光学成像系统与图像采集设备的物理限制,在疾病的病理研究和材料的表征中起着至关重要的作用。本文从信号分析的角度出发,将全息的记录与重建过程看作是复数域与实数域之间的转换,讨论全息重建的数学原理与物理实现过程,并以生物医学领域为应用导引,总结了全息成像的新挑战和机遇。

基于无透镜傅里叶变换数字全息的结构形貌测量

为了精确测量物体的形貌信息,提出了一种基于无透镜傅里叶变换数字全息的成像系统。首先,分析了无透镜傅里叶变换数字全息的成像原理,引入了倾斜平面校正方法;然后,搭建了成像系统平台,通过实验验证系统的成像性能。实验结果表明:系统的实际分辨率为57.02 lp/mm。测量结果的相对误差仅为3.95%,充分验证了该系统卓越的成像性能。

Quasi noise-free digital holography

One of the main drawbacks of Digital Holography(DH)is the coherent nature of the light source,which severely corrupts the quality of holographic reconstructions.Although numerous techniques to reduce noise in DH have provided good results,holographic noise suppression remains a challenging task.We propose a novel framework that combines the concepts of encoding multiple uncorrelated digital holograms,block grouping and collaborative filtering to achieve quasi noise-free DH reconstructions.The optimized joint action of these different image-denoising methods permits the removal of up to 98%of the noise while preserving the image contrast.The resulting quality of the hologram reconstructions is comparable to the quality achievable with non-coherent techniques and far beyond the current state of art in DH.Experimental validation is provided for both singlewavelength and multi-wavelength DH,and a comparison with the most used holographic denoising methods is performed.

End-to-end deep learning framework for digital holographic reconstruction

Digital holography records the entire wavefront of an object,including amplitude and phase.To reconstruct the object numerically,we can backpropagate the hologram with Fresnel–Kirchhoff integralbased algorithms such as the angular spectrum method and the convolution method.Although effective,these techniques require prior knowledge,such as the object distance,the incident angle between the two beams,and the source wavelength.Undesirable zero-order and twin images have to be removed by an additional filtering operation,which is usually manual and consumes more time in off-axis configuration.In addition,for phase imaging,the phase aberration has to be compensated,and subsequently an unwrapping step is needed to recover the true object thickness.The former either requires additional hardware or strong assumptions,whereas the phase unwrapping algorithms are often sensitive to noise and distortion.Furthermore,for a multisectional object,an all-in-focus image and depth map are desired for many applications,but current approaches tend to be computationally demanding.We propose an end-to-end deep learning framework,called a holographic reconstruction network,to tackle these holographic reconstruction problems.Through this data-driven approach,we show that it is possible to reconstruct a noise-free image that does not require any prior knowledge and can handle phase imaging as well as depth map generation.

Hiding an image in cascaded Fresnel digital holograms

A system of two separated computer-generated holograms termed cascaded Fresnel digital holography （CFDH） is proposed and its application to hiding information is demonstrated by a computer simulation experiment. The technique is that the reconstructed image is the result of the wave Fresnel diffraction of two sub-holograms located at different distances from the imaging plane along the illuminating beam. The two sub-holograms are generated by an iterative algorithm based on the projection onto convex sets. In the application to the hiding of optical information, the information to be hidden is encoded into the sub-hologram which is multiplied by the host image in the input plane, the other sub-hologram in the filter plane is used for the deciphering key, the hidden image can be reconstructed in the imaging plane of the CFDH setup.

Iterative projection meets sparsity regularization:towards practical single-shot quantitative phase imaging with in-line holography

Holography provides access to the optical phase.The emerging compressive phase retrieval approach can achieve in-line holographic imaging beyond the information-theoretic limit or even from a single shot by exploring the signal priors.However,iterative projection methods based on physical knowledge of the wavefield suffer from poor imaging quality,whereas the regularization techniques sacrifice robustness for fidelity.In this work,we present a unified compressive phase retrieval framework for in-line holography that encapsulates the unique advantages of both physical constraints and sparsity priors.In particular,a constrained complex total variation(CCTV)regularizer is introduced that explores the well-known absorption and support constraints together with sparsity in the gradient domain,enabling practical high-quality in-line holographic imaging from a single intensity image.We developed efficient solvers based on the proximal gradient method for the non-smooth regularized inverse problem and the corresponding denoising subproblem.Theoretical analyses further guarantee the convergence of the algorithms with prespecified parameters,obviating the need for manual parameter tuning.As both simulated and optical experiments demonstrate,the proposed CCTV model can characterize complex natural scenes while utilizing physically tractable constraints for quality enhancement.This new compressive phase retrieval approach can be extended,with minor adjustments,to various imaging configurations,sparsifying operators,and physical knowledge.It may cast new light on both theoretical and empirical studies.

Holographic 3D imaging through random media: methodologies and challenges

Imaging through random media continues to be a challenging problem of crucial importance in a wide range of fields of science and technology,ranging from telescopic imaging through atmospheric turbulence in astronomy to microscopic imaging through scattering tissues in biology.To meet the scope of this anniversary issue in holography,this review places a special focus on holographic techniques and their unique functionality,which play a pivotal role in imaging through random media.This review comprises two parts.The first part is intended to be a mini tutorial in which we first identify the true nature of the problems encountered in imaging through random media.We then explain through a methodological analysis how unique functions of holography can be exploited to provide practical solutions to problems.The second part introduces specific examples of experimental implementations for different principles of holographic techniques,along with their performance results,which were taken from some of our recent work.

离轴数字全息的正一级像自动重建方法

针对离轴数字全息中零级像和共轭像模糊重建像的问题,提出了一种基于峰值信噪比的自动提取正一级频谱并重建其图像的方法。理论上推演并分析了该方法的合理性和可行性,获知了频谱振幅的三个冲激函数点对应于正负一级和零级频谱中心。通过频谱图中的振幅极大值点可确定这三个中心点,然后利用圆形滤波窗提取正一级频谱,并以峰值信噪比为客观评价依据来确定最佳滤波窗半径和重建距离。实验结果表明,所提出的方法可以自动重建离焦全息图像的正一级像,与不滤波重建结果相比,其峰值信噪比提高了32.2%,且比全局阈值分步迭代法提高了7.6%。该方法不依赖于其他先验信息,为离轴全息频谱滤波算法提供了一种新的可行方案。

基于数字全息技术的透过散射介质的成像仿真

本文根据光的标量衍射理论,利用数字全息技术产生了包含散射介质共轭信息的物光共轭光,消除了散射介质的影响,并对散射介质内的目标物体进行清晰成像.对实际应用场景下的成像过程进行了分析和讨论,模拟了不同散射介质颗粒大小、物体与散射层不同间距下的成像效果,讨论了利用CCD和空间光调制器实现实时成像的可行性.