Imaging through scattering media is a common practice in many applications of biomedical imaging. Object image would deteriorate into unrecognizable speckle pattern when scattering media is presented. Many methods have been investigated to reconstruct the object image when only speckle pattern is available. In this paper, we demonstrate a method of single-shot imaging through scattering media. This method is based on classification and support vector regression of the measured speckle pattern. We prove the possibility of speckle pattern classification and related formulas are presented. The specified and limited imaging capability without speckle pattern classification is demonstrated. Our proposed approach, that is, speckle pattern classification based support vector regression method, makes up the deficiency. Experimental results show that, with our approach, speckle patterns could be utilized for classification when object images are unavailable, and object images can be reconstructed with high fidelity. The proposed approach for imaging through scattering media is expected to be applicable to various sensing schemes.

Imaging through scattering media using speckle pattern classification based support vector regression.

Fundamental challenge of imaging through a scattering media has been resolved by various approaches in the past two decades. Optical wavefront shaping technique is one such method in which one shapes the wavefront of light entering a scattering media using a wavefront shaper such that it cancels the scattering effect. It has been the most effective technique in focusing light inside a scattering media. Unfortunately, most of these techniques require direct access to the scattering medium or need to know the scattering properties of the medium beforehand. Through the novel scheme presented on this paper, both the illumination module and the detection are on the same side of the inspected object and the imaging process is a real time fast converging operation. We model the scattering medium being a biological tissue as a matrix having mathematical properties matched to the physical and biological aspects of the sample. In our adaptive optics scheme, we aim to estimate the scattering function and thus to encode the intensity of the illuminating laser light source using DMD (Digital Micromirror Device) with an inverse scattering function of the scattering medium, such that after passing its scattering function a focused beam is obtained. We optimize the pattern to be displayed on the DMD using Particle Swarm Algorithm (PSO) which eventually help in retrieving a 1D object hidden behind the media.

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Non-Invasive Imaging Through Scattering Medium by Using a Reverse Response Wavefront Shaping Technique.

We report coherent imaging of objects behind opaque scattering media with only one piece of the power spectrum pattern. We solve the unique solution and improve algorithm speed for the inverse problem. Based on the proposed scattering-disturbance model, with only one piece of the Fourier transform power spectrum pattern under coherent illumination, we successfully reconstruct clear images of the objects fully hidden by an opaque diffuser. The experimental results demonstrate the feasibility of the reconstruction method and the scattering-disturbance model. Our method makes it possible to carry out snapshot coherent imaging of the objects obscured by scattering media, which extends the methodology of x-ray crystallography to visible-light scattering imaging for underwater and living biomedical imaging.

Single-shot coherent power-spectrum imaging of objects hidden by opaque scattering media.

Wavefront sensing with a thin diffuser has emerged as a potential low-cost alternative to a lenslet array for aberrometry. Diffuser wavefront sensors (DWS) have previously relied on tracking speckle displacement and consequently require coherent illumination. Here we show that displacement of caustic patterns can be tracked for estimating wavefront gradient, enabling the use of incoherent light sources and large dynamic-range wavefront measurements. We compare the precision of a DWS to a Shack-Hartmann wavefront sensor (SHWS) when using coherent, partially coherent, and incoherent illumination, in the application of autorefraction. We induce spherical and cylindrical errors in a model eye and use a multi-level Demon's non-rigid registration algorithm to estimate caustic displacements relative to an emmetropic model eye. When compared to spherical error measurements with the SHWS using partially coherent illumination, the DWS demonstrates a $\sim$5-fold improvement in dynamic range (-4.0 to +4.5 D vs. -22.0 to +19.5 D) with less than half the reduction in resolution (0.072 vs. 0.116 D), enabling a $\sim$3-fold increase in the number of resolvable prescriptions (118 vs. 358). In addition to being 40x lower-cost, the unique, non-periodic nature of the caustic pattern formed by a diffuser enables a larger dynamic range of aberration measurements compared to a lenslet array.

Large dynamic range autorefraction with a low-cost diffuser wavefront sensor.

Wavefront sensing with a thin diffuser has emerged as a potential low-cost alternative to a lenslet array for aberrometry. Here we show that displacement of caustic patterns can be tracked for estimating wavefront gradient in a diffuser wavefront sensor (DWFS), enabling large dynamic-range wavefront measurements with sufficient accuracy for eyeglass prescription measurements. We compare the dynamic range, repeatability, precision, and number of resolvable prescriptions of a DWFS to a Shack-Hartmann wavefront sensor (SHWFS) for autorefraction measurement. We induce spherical and cylindrical errors in a model eye and use a multi-level Demon’s non-rigid registration algorithm to estimate caustic displacements relative to an emmetropic model eye. When compared to spherical error measurements with the SHWFS using a laser diode with a laser speckle reducer, the DWFS demonstrates a ∼5-fold improvement in dynamic range (−4.0 to +4.5 D vs. −22.0 to +19.5 D) with less than half the reduction in resolution (0.072 vs. 0.116 D), enabling a ∼3-fold increase in the number of resolvable prescriptions (118 vs. 358). In addition to being lower-cost, the unique, non-periodic nature of the caustic pattern formed by a diffuser enables a larger dynamic range of aberration measurements compared to a lenslet array.

The need to image objects through light-scattering materials is common in a range of applications. Different methods have been investigated to acquire the image of the object when diffusers are presented. In this paper, we demonstrate the object reconstruction with single-shot imaging based on the correlography principle and phase retrieval algorithm with coherent illumination. We prove the possibility of reconstructing positive and negative objects in both transmission and reflection modes with collimated and scattered light. Formulas for calculating the size of the object from the reconstructed image are presented. We also prove that the object can be retrieved from a small section of the raw speckle image. These interesting features will have broad potential applications in many areas (such as biomedicine, security and sensing).

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Lensless wide-field single-shot imaging through turbid media based on object-modulated speckles

The invention provides a high-precision three-dimensional measurement method and a measurement instrument. The measurement method comprises steps as follows: a rotating collection process of characteristic points; a calculation process of characteristic point coordinates; acquisition of a final measurement result. By means of the rotating collection process of the characteristic points, a rotary table is rotated to drive a sample to rotate repeatedly, positions of the characteristic points relative to a microlens array and arrangement of all the characteristic points on an element image are changed, so that all the characteristic points can be distinguished in the three-dimensional coordinate calculation stage and can be applied to calculation of three-dimensional coordinates, the problem that the characteristic points cannot be distinguished due to pixilation of an image sensor is solved, and the measurement precision is improved.

High-precision three-dimensional measurement method and measurement instrument

To measure large and heavy micro-structured workpieces in situ and improve the measurement accuracy, which strongly depends on the environment during the measurement of micro-structured surfaces, a workpiece rotating technique is proposed. This method utilizes the precise rotation of machine tools to drive the workpiece and records a set of elemental image arrays for the pickup stage to overcome the upper-resolution limit imposed by the Nyquist sampling theorem, which allows the increase in the two-dimensional spatial resolution of the computed depth images in integral imaging. By extracting the depth position, we can obtain accurate depth information and measurement results for micro-structured surfaces. We carried out simulations and experiments to demonstrate the proposed method, and the results show the feasibility of our method.

On-machine measurement method for micro-structured surface by integral imaging with workpiece rotating technique

To obtain satisfactory performance in characterizing optical freeform surfaces with local features, this paper proposes a model of a radial basis function with slope-based shape factor and distribution (RBF-SSD). Compared to previous RBF-slope models with only slope-based shape factors, the RBF-SSD model relates both shape factors and distribution with the surface slope, ensuring greater fitting ability can be achieved when fitting a surface with local features. Fitting experiments for two different surfaces demonstrated the fitting ability of the RBF-SSD model. An off-axis three-mirror system with 3  °    ×  3.6  °   field of view was designed as an example to show the optical design efficacy of our model.

Model of radial basis functions with slope-based shape factor and distribution for optical freeform surface

The study of imaging through scattering media especially 3D imaging is of great significance in many fields such as biomedical imaging. Recently, deep learning has been widely used in the field of information processing with its remarkable performance. In this paper, we proposed a method of three - dimensional imaging through scattering media based on deep learning. This method uses the deep neural network to process the information captured by the light field imaging system based on the microlens array, recovering the no-scattering 4D light field information, and then realize three-dimensional reconstruction by using the processed light field information. Deep learning method requires a large number of samples. But in many environments, it is difficult to obtain a large number of three-dimensional samples through experiment. To solve this crucial problem, we use incoherent light propagation model to simulate the light field propagation and generate samples which contains three-dimensional information through simulation. In this paper, we simulated the propagation of radiation emitted from objects behind a single layer of weak scattering media, generated a large number of samples of 4D light field information by simulation, trained the neural network and processed the test data set generated by simulation, and we realized the deblurring of the light field information which contains information of multiple layers of flat semitransparent objects, which could be used to realize the 3D reconstruction.

Lipei Song

Papers

Lensless wide-field single-shot imaging through turbid media based on object-modulated speckles

High-precision three-dimensional measurement method and measurement instrument

On-machine measurement method for micro-structured surface by integral imaging with workpiece rotating technique

Model of radial basis functions with slope-based shape factor and distribution for optical freeform surface

A method of 3D light field imaging through single layer of weak scattering media basd on deep learning