Image Reconstruction Of Objects Research Articles

Influence of Spatial Losses of the Signal Detected by a Single-Pixel Detector on the Quality of Object Image Reconstruction

Influence of Spatial Losses of the Signal Detected by a Single-Pixel Detector on the Quality of Object Image Reconstruction

Computational ghost imaging based on the conditional adversarial network

A framework of computational ghost imaging based on the conditional adversarial network is proposed to efficiently implement the reconstruction of object images in this research. Although the traditional ghost imaging can recover object images with a few amount of measured intensities and corresponding speckle patterns, the visual quality of reconstructed images is seriously influenced by a lot of noise. To solve this issue, a conditional adversarial network is designed to improve the quality of the noisy images reconstructed by the traditional ghost imaging. The objective function is composed of multiple loss metrics, which avoid suffering from training instability of the network. Especially, the combination of critic loss and gradient penalty metrics guarantees that a wide variety of network architectures are used as the generator and almost no hyperparameter tuning is required in the network. Most importantly, the proposed network can be trained with simulated data without spending a long time to collect the practical training samples and considering the experimental condition. After training, the parameters of the network such as kernel weights of convolution filters are optimized from the adversarial process between the generator and the discriminator, object images can be perfectly reconstructed at a very low sampling ratio. Through the simulated and optical experiments, it is demonstrated that the proposed method has much better performance than other methods such as the traditional and compressive-sensing-based methods.

Object recognition for remarkably small field-of-view with speckles

Object recognition conventionally requires a sufficiently large field of view that could fully encompass an object. However, we have discovered that, under coherent illumination, one can use a much smaller field of view for object recognition without loss of accuracy. This is because part of the speckle pattern related to an object contains some of its global information. Our approach can be applied to covert imaging and non-line-of-sight object recognition and image reconstruction.

Design of low-cost and simple reconstruction method for Three Dimensional Electrical Impedance Tomography (3D-EIT) Imaging

Electrical impedance tomography is a non-invasive imaging modality that uses the electrical conductivity distribution to reconstruct images based on potential measurements from the object's surface. The proposed study was to design and fabricate a low-cost and simple reconstruction method for 3D electrical impedance tomography imaging. In this study, we have been successfully developed 3 Dimensional Electrical Impedance Tomography (3D-EIT) system using 16 copper electrodes (Cu) to detect and reconstruct the presence of objects in the Phantom. 3D-EIT was developed using Phantom as a test object with PVC pipe material, with an inner diameter of 7.2 cm and a height of 5.4 cm. Electrodes were arranged in two rings, with each ring having eight electrodes arranged in a planar line. Furthermore, the Gauss-Newton algorithm and Laplace prior regularization were used to image reconstruction of objects inside the Phantom using voltage measurement produced from sequential pairs of neighboring electrodes. The voltage is obtained from the injection of a constant current of 1 mA at 20 kHz into the system's electrode pairs. The objects used in this research are PVC pipe, solid aluminum, PVC pipes filled with wax glue, and copper trusses. The results obtained show that the reconstruction results can provide information about the position, the electrical properties, and the shape of real objects. Finally, the system can detect the location, height, and electrical properties of objects for all variations of angle and height variations.

Energy-Based Dropout in Restricted Boltzmann Machines: Why Not Go Random

Deep learning architectures have been widely fostered throughout the last years, being used in a wide range of applications, such as object recognition, image reconstruction, and signal processing. Nevertheless, such models suffer from a common problem known as overfitting, which limits the network from predicting unseen data effectively. Regularization approaches arise in an attempt to address such a shortcoming. Among them, one can refer to the well-known Dropout, which tackles the problem by randomly shutting down a set of neurons and their connections according to a certain probability. Therefore, this approach does not consider any additional knowledge to decide which units should be disconnected. In this paper, we propose an energy-based Dropout (E-Dropout) that makes conscious decisions whether a neuron should be dropped or not. Specifically, we design this regularization method by correlating neurons and the model's energy as an importance level for further applying it to energy-based models, such as Restricted Boltzmann Machines (RBMs). The experimental results over several benchmark datasets revealed the proposed approach's suitability compared to the traditional Dropout and the standard RBMs.

Model-based dual-energy tomographic image reconstruction of objects containing known metal components

Dual-energy (DE) decomposition has been adopted in orthopedic imaging to measure bone composition and visualize intraarticular contrast enhancement. One of the potential applications involves monitoring of callus mineralization for longitudinal assessment of fracture healing. However, fracture repair usually involves internal fixation hardware that can generate significant artifacts in reconstructed images. To address this challenge, we develop a novel algorithm that combines simultaneous reconstruction-decomposition using a previously reported method for model-based material decomposition (MBMD) augmented by the known-component (KC) reconstruction framework to mitigate metal artifacts. We apply the proposed algorithm to simulated DE data representative of a dedicated extremity cone-beam CT (CBCT) employing an x-ray unit with three vertically arranged sources. The scanner generates DE data with non-coinciding high- and low-energy projection rays when the central source is operated at high tube potential and the peripheral sources at low potential. The proposed algorithm was validated using a digital extremity phantom containing varying concentrations of Ca-water mixtures and Ti implants. Decomposition accuracy was compared to MBMD without the KC model. The proposed method suppressed metal artifacts and yielded estimated Ca concentrations that approached the reconstructions of an implant-free phantom for most mixture regions. In the vicinity of simple components, the errors of Ca density estimates obtained by incorporating KC in MBMD were ∼1.5–5× lower than the errors of conventional MBMD; for cases with complex implants, the errors were ∼3–5× lower. In conclusion, the proposed method can achieve accurate bone mineral density measurements in the presence of metal implants using non-coinciding DE projections acquired on a multisource CBCT system.

Method of Object Image Reconstruction Using a Circular Antenna Array

The method for reconstructing object images in cross-sections using a circular antenna array when sounding space by an ultrasonic monochromatic wave is proposed. The image reconstruction is carried out by scanning the internal structure of the object placed inside the circle controlled by the focus of the circular antenna array. An algorithm for controlling the phase shift modules in the elementary radiator channels of the circular antenna array for changing the focus position is presented. Model results of the reconstruction of the image of the simplest point objects are presented. The problems of implementation of a circular array are discussed.

Imaging through scattering media based on semi-supervised learning.

We present a method for less-invasive imaging through scattering media. We use an image-to-image translation, which is called a cycle generative adversarial network (CycleGAN), based on semi-supervised learning with an unlabeled dataset. Our method was experimentally demonstrated by reconstructing object images displayed on a spatial light modulator between diffusers. In the demonstration, CycleGAN was trained with captured images and object candidate images that were not used for image capturing through the diffusers and were not paired with the captured images.

A family portrait of disk inner rims around Herbig Ae/Be stars

Context. The innermost astronomical unit (au) in protoplanetary disks is a key region for stellar and planet formation, as exoplanet searches have shown a large occurrence of close-in planets that are located within the first au around their host star. Aims. We aim to reveal the morphology of the disk inner rim using near-infrared interferometric observations with milli-arcsecond resolution provided by near-infrared multitelescope interferometry. Methods. We provide model-independent reconstructed images of 15 objects selected from the Herbig AeBe survey carried out with PIONIER at the Very Large Telescope Interferometer, using the semi-parametric approach for image reconstruction of chromatic objects. We propose a set of methods to reconstruct and analyze the images in a consistent way. Results. We find that 40% of the systems (6/15) are centrosymmetric at the angular resolution of the observations. For the rest of the objects, we find evidence for asymmetric emission due to moderate-to-strong inclination of a disk-like structure for ~30% of the objects (5/15) and noncentrosymmetric morphology due to a nonaxisymmetric and possibly variable environment (4/15, ~27%). Among the systems with a disk-like structure, 20% (3/15) show a resolved dust-free cavity. Finally, we do not detect extended emission beyond the inner rim. Conclusions. The image reconstruction process is a powerful tool to reveal complex disk inner rim morphologies, which is complementary to the fit of geometrical models. At the angular resolution reached by near-infrared interferometric observations, most of the images are compatible with a centrally peaked emission (no cavity). For the most resolved targets, image reconstruction reveals morphologies that cannot be reproduced by generic parametric models (e.g., perturbed inner rims or complex brightness distributions). Moreover, the nonaxisymmetric disks show that the spatial resolution probed by optical interferometers makes the observations of the near-infrared emission (inside a few au) sensitive to temporal evolution with a time-scale down to a few weeks. The evidence of nonaxisymmetric emission that cannot be explained by simple inclination and radiative transfer effects requires alternative explanations, such as a warping of the inner disks. Interferometric observations can therefore be used to follow the evolution of the asymmetry of those disks at an au or sub-au scale.

Extreme ultraviolet lensless imaging without object support through rotational diversity in diffractive shearing interferometry.

We report on a method that allows microscopic image reconstruction from extreme-ultraviolet diffraction patterns without the need for object support constraints or other prior knowledge about the object structure. This is achieved by introducing additional diversity through rotation of an object in a rotationally asymmetric probe beam, produced by the spatial interference between two phase-coherent high-harmonic beams. With this rotational diffractive shearing interferometry method, we demonstrate robust image reconstruction of microscopic objects at wavelengths around 30 nm, using images recorded at only three to five different object rotations.

Object Removal Software Test Automation

This paper considers the problem of designing a test method and robust test automation for evaluating the functionality of computer vision algorithms for object removal and image reconstruction of the removed area. An object removal algorithm is used to select and remove a region in an image. After the removal of the object, the object removal algorithm regenerates the area in the image from which the object was removed, similar to photoshop. We developed an algorithm in MATLAB that accesses the features of the macroblocks from the region that adjoins the removed object and correlates these macroblocks with the actual area that is regenerated. The SSIM (structural similarity index) score is calculated by comparing the ground truth with the image generated from image reconstruction after removal of the object. Finally, we calculate the artifact area present in the regenerated region to determine the algorithm quality. To validate this method, the authors compare a 3rd-party object removal solution with an in-house developed solution using the proposed approach. This comparison shows that the SSIM score is 1.55% higher than the 3rd-party solution and 26.3% lower in artifact areas. Besides the results, this paper also describes in detail the procedure to automate the use case of object removal test automation to scale up the test coverage.

A robust fast variable-aperture Fourier ptychography

We report a novel variable-aperture Fourier ptychography based on a 4-f optical correlator for reconstructing high-resolution images from a few captured low-resolution images. With various overlapping apertures filtering the spatial spectrum, the outputs of the correlator are captured as the low-resolution images for reconstructing object images. The simulations and the experiments with a DMD for providing the variable apertures demonstrate that, the reported scheme is tolerant to aperture’s inaccurate positioning and shape error. Furthermore, rather than mechanical aperture-scanning, the scheme takes much less time for reconstructing object images. Compared with other Fourier ptychography methods, the reported scheme will be more prospective for wide applications in various imaging fields.

Non-destructive ghost authentication for single-pixel imaging in mass user environment

A secured ghost imaging system can be constructed in a big data environment by generating many ciphertext sequences (including both correct and incorrect ones) from different object images and only allowing authorized users to retrieve the target correct ones. In such schemes, the identification of the truth of the ciphertext is a critical issue. In previous works, a ciphertext authentication scheme for a ghost imaging system was proposed by embedding ciphertext fractions generated from hidden images into the target object ciphertext sequence. However, the substituted ciphertext elements will cause severe degradation in the reconstructed object image quality, especially when a large number of hidden images are employed in a mass user environment. In this paper, we propose a non-destructive ciphertext authentication scheme by recording the positions of the ciphertext elements with similar intensities to form the authentication key, rather than direct embedding. Our proposed scheme has a significant advantage over the previous destructive authentication scheme by preserving the fidelity of the reconstructed object image when the ciphertext is authenticated by many users simultaneously.

Calibrated Phase-Shifting Digital Holographic Microscope Using a Sampling Moiré Technique

A calibrated phase-shifting digital holographic microscope system capable of improving the quality of reconstructed images is proposed. Phase-shifting errors are introduced in phase-shifted holograms for numerous reasons, such as the non-linearity of piezoelectric transducers (PZTs), wavelength fluctuations in lasers, and environmental disturbances, leading to poor-quality reconstructions. In our system, in addition to the camera used to record object information, an extra camera is used to record interferograms, which are used to analyze phase-shifting errors using a sampling Moiré technique. The quality of the reconstructed object images can be improved by the phase-shifting error compensation algorithm. Both the numerical simulation and experiment demonstrate the effectiveness of the proposed system.

Three-dimensional image reconstruction of macroscopic objects from a single digital hologram using stereo disparity.

We present depth extraction of macroscopic three-dimensional (3D) objects from a single digital hologram using stereo disparity. The method does not require the phase information of the hologram but two perspectives of the scene, which are easily obtained by dividing the hologram into two parts (two apertures) before the reconstruction. Variation of the hologram division is countless since each piece of a single hologram contains all the information regarding the scene; therefore, stereo disparity can be calculated along any arbitrary direction. We investigated the effects of gradual and sharp divisions of the holograms for the disparity map calculations, specifically for divisions in the vertical, horizontal, and diagonal directions. After obtaining the depth map from the stereo images, a regular two-dimensional image of the object is merged with the depth information to form 3D visualization of the object. Holograms were recorded with a rigid endoscope, and experimentally obtained depth profiles of the objects are in very good agreement with the actual profiles.

Sonar image reconstruction of objects near a reflective boundary

The properties of reconstructed acoustic images, created from data obtained using backscattering synthetic aperture sonar (SAS) systems, have been studied for objects in the free field. The presence of a nearby reflecting boundary, such as the seafloor or surface, greatly increases the number of mechanisms or raypaths by which sound may be backscattered to the sonar system. Some of these raypaths involve one or more interactions with the reflecting boundary (multipaths), and others involve sound scattering multiple times from the same target (multiple scattering). Experiments were conducted using an air-water interface and simple cylindrical targets in order to examine the properties of the reconstructed circular SAS (CSAS) images, including effects due to vertical obliquity of the target [D. Plotnick et al., J. Acoust. Soc. Am. 137, 470-480 (2015)]. The CSAS image is by definition a two-dimensional representation of three-dimensional scattering; the image is thus highly dependent on the object’s 3-D shap...

Three-dimensional image reconstruction of objects using synthetic aperture sonar

Synthetic aperture sonar imaging is typically considered for the case of linear or circular scans, where the reconstructed acoustic image is a two-dimensional representation of the true three-dimensional scattering from some object. However, a multi-dimensional aperture may be used to create a 3-D or volume image reconstruction of the acoustic scattering by that object. The 3-D image reconstruction may be performed using a delay-and-sum algorithm, or using comparatively fast wavenumber based methods. Simulated point scatterers will be used to initially demonstrate the algorithms, followed by a demonstration involving a simple object near a reflecting boundary. For objects that are located close to a reflecting boundary there exists a rich 3-D scattering structure. When imaged in two dimensions, object features becomes distorted due to the projection of scattering loci (e.g. the broadside reflection from a cylindrical target) that may be located outside of the image plane [Plotnick et al., J. Acoust. Soc. ...

Effect of the radiation pattern on the quality of object image reconstruction in circular aperture synthesis

This paper addresses the problem of the acoustic wave reception sector of a tomograph detector in an aqueous medium, whose solution anticipates the development of a tomograph with circular aperture synthesis in monochromatic probing. In the theoretical consideration of the problem of object image reconstruction, the transducer radiation pattern was assumed to be isotropic in the plane, i. e. disk-shaped, with an unlimited circular reception sector, which allows investigation of the internal structure of the object in the plane of the radiation pattern disk. The effect of the deviation from isotropy due to the limitation of the acoustic wave reception sector on the results of image reconstruction of a point object is determined by modeling the reconstruction of a point object image from trajectory Doppler signals received by the detector moving on a circular path around the point object.

Depth-of-focus Resolution and Viewing Angle Improvement of Integral Imaging System Using Multi-directional Projections and Non-uniform Lenslets Array with Intermediate View Reconstruction Method

This study presents a three-dimensional (3-D) integral imaging system to improve concurrently the viewing angle, Depth-Of-Focus (DOF) and resolution of the reconstructed object images by using multi-directional projections and non-uniform lenslets array with Intermediate-View Reconstruction Method (IVRM). In this method, each elemental lens array collects multi-directional illuminations of multiple Elemental Image (EI) sets and generates multiple Point Light Sources (PLSs) at the different positions in the two focal planes. The viewing zone and depth-of-focus is larger than the conventional method because of multi-directional projections of multiple EI sets and non-uniform lenslets; whereas a conventional method produces a viewing zone using only a single set of EI projection and uniform lenslets. For the non-uniform lenslets, DOF-improved integral images of 3-D objects can be picked-up and then by applying the IVRM to these picked-up integral images. Hence, the viewing angle, DOF as well as resolution enhanced object images can be reconstructed. To find out the possibility of the proposed system, experimental results are discussed with mathematical expressions.

Detecting Lateral Motion using Light's Orbital Angular Momentum.

Interrogating an object with a light beam and analyzing the scattered light can reveal kinematic information about the object, which is vital for applications ranging from autonomous vehicles to gesture recognition and virtual reality. We show that by analyzing the change in the orbital angular momentum (OAM) of a tilted light beam eclipsed by a moving object, lateral motion of the object can be detected in an arbitrary direction using a single light beam and without object image reconstruction. We observe OAM spectral asymmetry that corresponds to the lateral motion direction along an arbitrary axis perpendicular to the plane containing the light beam and OAM measurement axes. These findings extend OAM-based remote sensing to detection of non-rotational qualities of objects and may also have extensions to other electromagnetic wave regimes, including radio and sound.