Speckle Intensity Research Articles

High-visibility calculating ghost imaging with self-reconstruction capability and extendible depth-of-field

We customized light speckle fields with both super-bunching and non-diffracting properties, accordingly named as the super-bunching, non-diffracting (SP-ND) speckle fields, by introducing pupil function of a ring aperture with azimuthally correlated phases in the vertically opposite angles. Calculating ghost imaging based on the SP-ND speckle fields was demonstrated to be of higher visibility, higher spatial resolution and larger depth of field than that based on the conventional speckle fields such as pseudo-thermal fields. Interestingly, the SP-ND speckles are also of self-healing capability in respect of not only the speckle intensity distribution but also the high-order coherence properties. Therefore, even when the SP-ND speckle fields are seriously disturbed, for example, blocked partially by an opaque obstacle, ghost images are able to be reconstructed once the object is placed in the self-healed speckle fields.

Increasing the raw contrast of VLT/SPHERE with the dark hole technique

Context. Imaging exoplanetary systems is essential to characterizing exoplanet atmospheres and orbits as well as circumstellar disks and to studying planet-disk interactions to understand the planet formation processes. Imaging exoplanets or circumstellar disks in the visible and near-infrared is challenging, however, because these objects are very faint relative to their star, even though only fractions of an arcsecond away. Coronagraphic instruments have already allowed the imaging of a few exoplanets, but their performance is limited by wavefront aberrations. Adaptive optics systems partly compensate for the Earth’s atmosphere turbulence, but they cannot fully control the wavefront. Some of the starlight leaks through the coronagraph and forms speckles in the astrophysical image. Focal plane wavefront control, used as a second stage after the adaptive optics system, has been proposed to minimize the speckle intensity within an area called the dark hole. Aims. We previously demonstrated the on-sky performance of dark hole techniques, pairwise probing coupled with electric field conjugation, using the apodized pupil Lyot coronagraph of the VLT/SPHERE instrument. In this paper, we probe their performance using the SPHERE four-quadrant phase mask coronagraph, and we demonstrate the interest of combining dark hole techniques and reference differential imaging. Methods. We used these dark hole techniques on-sky to create a dark hole in the narrow band around 1.7 |j.m observing HR 4796. We then recorded broadband images of HR 4796 and a reference star at the H band. Results. The dark hole techniques improved the H-band detection limit by a factor of three. The dark hole was stable from one star to a nearby star enabling reference differential imaging. Conclusions. This stability offers two new strategies of observation. First, one can quickly create a dark hole observing a bright star before pointing to a faint target star. Furthermore, one can couple dark hole techniques and reference differential imaging. A very interesting point is that the performance of these methods does not depend on the astrophysical signal.

EH-former: Regional easy-hard-aware transformer for breast lesion segmentation in ultrasound images

Breast lesion segmentation of ultrasound images plays a crucial role in early screening and diagnosis of breast lesions. However, accurately segmenting lesions in breast ultrasound (BUS) images is challenging due to prevalent issues such as low contrast, intense speckle noise, and blurred lesion boundaries. Although existing deep learning-based segmentation models have made significant progress, few have strategically addressed these complex and noisy regional features in BUS images. The easy-to-hard manner in Curriculum Learning (CL) appears promising, but it often remains at the sample level and does not adequately address regional complexities. To address this, we design a region-wise CL to dynamically adjust the focus on hard regional features in BUS images. Specifically, we propose a Regional Easy-Hard-Aware Transformer (EH-Former), structured in two stages for lesion segmentation in BUS images. The first stage incorporates uncertainty estimation for dividing regional difficulty. In the second stage, we propose a novel Adaptive Easy-Hard region Separator (AdaSep), a module employing uncertainty-aware regularization to separate features of varying difficulties, allowing the two streams within EH-Former to focus on learning regional features of different complexities. Additionally, we develop a Dynamic Easy-Hard Feature Fusion (D-Fusion) module, dynamically adjusting the fusion weight of easy and hard regional features based on the current training epoch to achieve progressive regional feature learning. Extensive experimental results on five public datasets show that the proposed EH-Former consistently outperforms state-of-the-art methods in most metrics and exhibits better domain generalization capabilities. Furthermore, our region-wise CL significantly enhances the performance of EH-Former in detecting complex tissue structures and noisy areas that are challenging to segment accurately. The source code is available at https://github.com/lele0109/EH-Former.

Validation of the Openwater wearable optical system: cerebral hemodynamic monitoring during a breath-hold maneuver.

Bedside cerebral blood flow (CBF) monitoring has the potential to inform and improve care for acute neurologic diseases, but technical challenges limit the use of existing techniques in clinical practice. Here, we validate the Openwater optical system, a novel wearable headset that uses laser speckle contrast to monitor microvascular hemodynamics. We monitored 25 healthy adults with the Openwater system and concurrent transcranial Doppler (TCD) while performing a breath-hold maneuver to increase CBF. Relative blood flow (rBF) was derived from changes in speckle contrast, and relative blood volume (rBV) was derived from changes in speckle average intensity. A strong correlation was observed between beat-to-beat optical rBF and TCD-measured cerebral blood flow velocity (CBFv), ; the slope of the linear fit indicates good agreement, 0.87 (95% CI: 0.83 ). Beat-to-beat rBV and CBFv were also strongly correlated, , but as expected the two variables were not proportional; changes in rBV were smaller than CBFv changes, with linear fit slope of 0.18 (95% CI: 0.17 to 0.19). Further, strong agreement was found between rBF and CBFv waveform morphology and related metrics. This first in vivo validation of the Openwater optical system highlights its potential as a cerebral hemodynamic monitor, but additional validation is needed in disease states.

Dynamic light scattering and laser speckle contrast imaging of the brain: theory of the spatial and temporal statistics of speckle pattern evolution.

Dynamic light scattering (DLS) and laser speckle contrast imaging (LSCI) are closely related techniques that exploit the statistics of speckle patterns, which can be utilized to measure cerebral blood flow (CBF). Conventionally, the temporal speckle intensity auto-correlation function is calculated in DLS, while the spatial speckle contrast Ks is calculated in LSCI measurements. Due to the rapid development of CMOS detection technology with increased camera frame rates while still maintaining a large number of pixels, the ensemble or spatial average of as well as the temporal contrast Kt can be easily calculated and utilized to quantify CBF. Although many models have been established, a proper summary is still lacking to fully characterize DLS and LSCI measurements for spatial and temporal statistics, laser coherence properties, various motion types, etc. As a result, there are many instances where theoretical models are misused. For instance, mathematical formulas derived in the diffusive regime or for ergodic systems are sometimes applied to small animal brain measurements, e.g., mice brains, where the assumptions are not valid. Therefore, we aim to provide a review of the speckle theory for both DLS and LSCI measurements with detailed derivations from first principles, taking into account non-ergodicity, spatial and temporal statistics of speckles, scatterer motion types, and laser coherence properties. From these calculations, we elaborate on the differences between spatial and temporal averaging for DLS and LSCI measurements that are typically ignored but can result in inaccurate measurements of blood flow, particularly the spatially varying nature of the static component in and Kt. We also obtained maps in in vivo mouse brain measurements using high frame rate CMOS cameras which have not been demonstrated before, and compared with and Ks,t. This work provides a useful guide for choosing the correct model to analyze spatial and temporal speckle statistics in in-vivo DLS and LSCI measurements.

Echo scattering characteristics: Vortex beams reflected by rough surface in ocean turbulence

Optical field echo scattering characteristic is one of the essential technologies for the future integration of underwater laser communication and detection. Vortex beam (e.g. Laguerre-Gaussian (LG) beam) with a helical wavefront structure is better suited to reduce the effects of ocean turbulence. A double-path transmission model of LG beam scattering through rough surface in ocean turbulence is innovatively established. We developed a closed analytical expression for the echo speckle intensity of LG beams reflected by a rough surface with a Gaussian distribution in ocean turbulence based on the generalized Huygens-Fresnel principle. The autocorrelation function of intensity and complex degree of coherence (DOC) of echo speckle field were numerically simulated and analyzed. From the results we found a rule that when coherence length of rough surfaces (ρh) is greater than the coherence length (ρ0) of spherical waves propagating across ocean turbulence, the impact of a rough surface on DOC is much less than that of ocean turbulence. This conclusion provides the theoretical basis that the echo wave field cannot be obtained in target detection under ocean turbulence.

Lensless multi-core-fiber-based imaging from speckle autocorrelation under highly coherent illumination

Flexible fiber-optic lensless endoscopic imaging plays a significant role in medical and biological applications. Lensless imaging based on far-field speckle of multi-core fibers under spatially incoherent light source illumination relied on the angular optical memory effect, resulting in limited field of view and susceptibility to interference effects. Image reconstruction from fiber speckle intensity under the highly coherent light illumination has been investigated using classical coherent diffraction theory, but it imposes limitations on imaging distance and detection positions. However, existing alternative solutions involve reducing coherence level to satisfy the angular optical memory effect, which increases system complexity and sacrifices the advantages of single-frame imaging. The reconstruction of intensity-based images remains a significant challenge under highly coherent illumination, primarily due to the interference effect. In this study, an imaging algorithm that reconstructs the original image solely from the intensity of far-field fiber speckle under coherent illumination conditions is proposed. The proposed method is based on statistical optics theory and aims to extract the relevant information within coherent speckle patterns to reconstruct the image. Our approach expands the imaging field of view, simplifies the imaging setup, and broadens the range of viable light sources for speckle correlation imaging. The effectiveness of the algorithm is verified by simulated experiments and a real imaging system.

Direct measurement of the structural change associated with amorphous solidification using static scattering of coherent radiation.

In this paper, we demonstrate that the weak temperature dependence of the structure factor of supercooled liquids, a defining feature of the glass transition, is a consequence of the averaging of the scattering intensity due to angular averaging. We show that the speckle at individual wavevectors, calculated from a simulated glass former, exhibits a Debye-Waller factor with a sufficiently large temperature dependence to represent a structural order parameter capable of distinguishing liquid from glass. We also extract from the speckle intensities a quantity proportional to the variance of the local restraint, i.e., a direct experimental measure of the amplitude of structural heterogeneity.

Real time characterization of atmospheric turbulence using speckle texture

A new method is proposed for the characterization of the atmospheric turbulence strength parameter () based on the principal component analysis (PCA) of the texture of the speckle intensity pattern obtained on long-range propagation of a focused charge +1 vortex beam. Employing the split-step propagation method, datasets containing instantaneous intensity images of the focused vortex beam are generated for three distinct values, specifically , , and , representing medium to high turbulence levels for a 2 km propagation distance. The gray level co-occurrence matrix (GLCM) methodology is employed to extract key texture attributes, like contrast, correlation, homogeneity, and energy from the intensity images. These extracted texture parameters serve as inputs for training a PCA model, enabling the identification of associated values. The PCA analysis exhibits distinct clustering of the first three principal components for each of the three values, forming individual clusters on the PCA plot. Standard deviational ellipses are drawn to clearly demarcate these clusters on the PCA plot. The texture-based PCA classification of atmospheric turbulence was also performed for a focused Gaussian beam. The comparison of PCA plots between vortex and Gaussian beams showed that a pronounced clear separation of values is obtained for the vortex beam. This indicates that the non-zero orbital angular momentum of the vortex beam also plays an important role in achieving the distinct separation of values on the PCA plot. The proposed method can provide efficient real-time turbulence estimation solely on the basis of texture of the instantaneous intensity speckle with prior training and therefore may simplify the estimation of turbulence strength parameter.

Spectral speckle customization

Speckle patterns are used in a broad range of applications including microscopy, imaging, and light–matter interactions. Tailoring speckles’ statistics can dramatically enhance their performance in applications. We present an experimental technique for customizing the spatio-spectral speckled intensity statistics of optical pulses at the output of a complex medium (a disordered multimode fiber) by controlling the spatial profile of the input light. We demonstrate that it is possible to create ensembles of independent speckle patterns with arbitrary statistics at a single wavelength, simultaneously at multiple decorrelated wavelengths, and even tailored statistics across an entire pulse spectrum.

Extreme detectable vibration frequency limited by rolling shutter camera imaging of laser speckles.

The row scanning mechanism of a rolling shutter camera can be used to infer high-frequency information from a low-frame-rate video. Combining the high intensity of laser speckle and high row-sampling rate of a rolling shutter, extreme detectable vibration frequency limited by rolling shutter camera imaging is experimentally demonstrated. Using a commercially available industrial camera at a frame rate of 70 fps, a vibration signal with a frequency of 14.285 kHz is extracted that corresponds to an inter-row sampling period of 35 µs and a sampling frequency of 28.57 kHz. Connected component and centroid alignment algorithms are used to extract the inter-row vibration displacement. The parameters that limit the highest and lowest detectable frequencies are discussed.

Orbital angular momentum mode fiber force sensing technology based on intensity interrogation.

Micromanipulation and biological, materials science, and medical applications often require controlling or measuring the forces exerted on small objects. Based on the high linearity and sensitivity of OAM beams in the sensing field, this article proposes for the first time to apply OAM beams to force sensing. In this paper, a fiber optic force sensing technology based on the intensity distribution change of orbital angular momentum (OAM) mode is proposed and realized. This technique detects the magnitude of the external force applied to the fiber by exciting the OAM mode with a topological charge 3, thereby tracking changes in light intensity caused by mode coupling. Applying this technique to force measurement, we have experimentally verified that when the sensor is subjected to a force in the range of 0mN to 10mN, the change in speckle light intensity at the sensor output has a good linear relationship with the force. Meanwhile, theoretical analysis and experimental results indicate that compared with previous force sensing methods, this sensing technology has a simple structure, is easy to implement, has good stability, and has practical application potential.

Multimodal optical device to study dynamics of drying process

Imaging and quantification of the drying process find applications in many fields, including the drying of paints. Measurement of different parameters during the drying process leads to accurate identification of the state of the sample under investigation. We propose a multimodal optical technique combining spectroscopy, speckle correlation, and digital holography to analyze and quantify drying process. The developed device is tested in the identification of drying phases of paints. In the developed device, digital holographic interferometry is employed to obtain spatial variation of deformation on the surface coated with paint. Although digital holography is an efficient tool to study drying it is limited to the latter stages of the process. To study initial and intermediate stages laser speckle correlation and spectroscopy are integrated with digital holography. The spectrometer uses an LED source to acquire the reflectance spectrum. The reflectance increases with time and saturates as the water content of paint naturally evaporates. It was observed that this saturation occurs in intermediate stages of the process. To further analyze the drying stages, speckle images of the paint surface are also acquired. The speckle intensity correlation varied from low to high with drying. The combination of laser speckle, digital holography and spectroscopy complement one another and enables the study of all stages of drying process. To the best of our knowledge this is the first time such a multimodal optical device is developed for the complete analysis of drying process.

Scattered-light-sheet microscopy with sub-cellular resolving power.

Since its first demonstration over 100 years ago, scattering-based light-sheet microscopy has recently re-emerged as a key modality in label-free tissue imaging and cellular morphometry; however, scattering-based light-sheet imaging with subcellular resolution remains an unmet target. This is because related approaches inevitably superimpose speckle or granular intensity modulation on to the native subcellular features. Here, we addressed this challenge by deploying a time-averaged pseudo-thermalized light-sheet illumination. While this approach increased the lateral dimensions of the illumination sheet, we achieved subcellular resolving power after image deconvolution. We validated this approach by imaging cytosolic carbon depots in yeast and bacteria with increased specificity, no staining, and ultralow irradiance levels. Overall, we expect this scattering-based light-sheet microscopy approach will advance single, live cell imaging by conferring low-irradiance and label-free operation towards eradicating phototoxicity.

CDM: A coupled deformable model for image segmentation with speckle noise and severe intensity inhomogeneity

Speckle noise and intensity inhomogeneity are always challenging issues in the area of image segmentation, especially when both difficulties appear simultaneously. Consequently, the majority of existing deformable models yield inadequate results in this situation. This paper aims to address these issues by combining a bias correction term and a despeckling term into a single variational level set architecture, which not only corrects the severe intensity inhomogeneity but also performs image despeckling and segmentation simultaneously. Specifically, edge and region synergetic terms are defined to correct the severe intensity inhomogeneity during image segmentation that eradicates their shortcomings as well as retains their advantages. Further, a despeckling term is constructed, which effectively suppresses the noise while enhancing image details. Since the lack of thorough investigation on despeckling of images degraded by Rayleigh noise distribution, which usually appear in ultrasound (US) images, so we included it in the coupled deformable model (CDM). Moreover, region-based terms eradicate complex re-initialization and numerical instability during the level set evolution, as a result, no distance regularization term is needed. Additionally, Schauder’s fixed point theorem is used to demonstrate the well-posedness of the present system. Extensive numerical experiments on real and synthetic images with speckle noise and severe inhomogeneous intensity demonstrate that the CDM exhibits superior results compared to classical and some recent deformable models in terms of accuracy, robustness, and various quality measures.

Speckle-based structured light shift-keying for non-line-of-sight optical communication.

We report an experimental proof of concept for speckle-based one-to-three non-line-of-sight (NLOS) free space optical (FSO) communication channels employing structured light shift-keying. A 3-bit gray image of resolution 100×100 pixels is encoded in Laguerre-Gaussian or Hermite-Gaussian beams and decoded using their respective intensity speckle patterns via trained 1D convolutional neural network. We have achieved an average classification accuracy of 96% and 93% using L G ml and H G pq beams, respectively, among all three channels. It demonstrates the directional independence and broadcasting capability of speckle-based decoding (SBD) in FSO communication using structured light. Further, we have extended the study from 2D to 1D SBD in one-to-three NLOS FSO communication channels to decrease the computational cost and to emphasize the importance of the 1D SBD approach.

Direct high-resolution X-ray imaging exploiting pseudorandomness

Owing to its unique penetrating power and high-resolution capability, X-ray imaging has been an irreplaceable tool since its discovery. Despite the significance, the resolution of X-ray imaging has largely been limited by the technical difficulties on X-ray lens making. Various lensless imaging methods have been proposed, but are yet relying on multiple measurements or additional constraints on measurements or samples. Here we present coherent speckle-correlation imaging (CSI) using a designed X-ray diffuser. CSI has no prerequisites for samples or measurements. Instead, from a single shot measurement, the complex sample field is retrieved based on the pseudorandomness of the speckle intensity pattern, ensured through a diffuser. We achieve a spatial resolution of 13.9 nm at 5.46 keV, beating the feature size of the diffuser used (300 nm). The high-resolution imaging capability is theoretically explained based on fundamental and practical limits. We expect the CSI to be a versatile tool for navigating the unexplored world of nanometer.

Speckle-learned convolutional neural network for the recognition of intensity degenerate orbital angular momentum modes

Intensity degenerate orbital angular momentum (OAM) modes are impossible to recognize by direct visual inspection even using available machine learning techniques. We are reporting speckle-learned convolutional neural network (CNN) for the recognition of intensity degenerate Laguerre–Gaussian (LGp , l) modes, intensity degenerate LG superposition modes, and intensity degenerate perfect optical vortices. The CNN is trained on the simulated one-dimensional far-field intensity speckle patterns of the corresponding intensity degenerate OAM modes. The trained CNN recognizes intensity degenerate OAM modes with an accuracy >99 % . Speckle-learned CNNs are also capable of recognizing intensity degenerate OAM modes even under the presence of high Gaussian white noise and atmospheric turbulence with an accuracy >97 % .

Single-shot generalized Hanbury Brown-Twiss experiments using a polarization camera for target intensity reconstruction in scattering media.

To see through a random light field in real-time, single-shot generalized Hanbury Brown-Twiss experiments using a polarization camera are proposed. The target intensity distribution is obtained from a complex coherence function which is calculated from auto-correlation and cross correlation functions of phase-shifted speckle intensity distributions. The phase-shifted speckle intensity distributions are simultaneously obtained through a strategy of parallel phase-shifting digital holography. Experimental results show that the proposed method can image a moving object in a random light field using a measured complex coherence function through the van Cittert-Zernike theorem.

Spatiotemporal characteristics of dynamic speckle from a 3D target in atmospheric turbulence

Spatiotemporal correlation function is the basic characteristic of dynamic laser speckle and the basis of various applications. The correlation function of the speckle intensity from a 3D target in turbulent atmosphere is derived based on the model of random phase screen and Fresnel Kirchhoff Diffraction Formula, and a fast algorithm based on FFT is developed. The particularity of dynamic speckle in turbulence is numerically analyzed and discussed. The results show that the speckle intensity fluctuates at two independent scales both in space and time domain, which are affected by target size and atmospheric turbulence respectively. In particular, the time scale caused by turbulence is also affected by the target translating velocity and the wind direction. The theory and algorithm developed in this paper can play important roles in applications of laser speckle such as remote detection in atmospheric environment.