Image Distance Research Articles

Research progress of correlation imaging under outdoor environment

Image, as a method of information acquisition, is indispensable for human beings, and it plays an irreplaceable role in military and civilian fields, such as detection and scouting, precision guidance, transportation, and industrial production. In the outdoor environment, the resolution, signal-to-noise ratio, and working distance of optical imaging are limited as result of the influence of background light, stray light, and atmospheric medium. In recent years, with the development of muti-discipline such as optics, physics, information theory, and computer science, the new optical imaging technologies continue to emerge, thus bringing new opportunities for outdoor optical imaging towards long-distance, large field of view and high information flux. As one of the new active imaging technologies, correlation imaging has the potential applications of robustness against turbulence and noise, and the possibility of beating the Rayleigh limit. It can deal with the problems better, such as sharp attenuation of optical power caused by long distances, detection of interference signals from environmental noise, and influence of turbulence. Based on the principle of optical imaging, this paper analyzes the factors affecting optical imaging, in terms of resolution, signal-to-noise ratio, spatial bandwidth product, and imaging distance under outdoor environment, focusing on the research progress of outdoor correlation imaging including imaging systems, signal-to-noise screening technology and imaging algorithm. In addition, we analyze the requirements of optical imaging for longer distances and broader field of view, and consider the fundamental problems and the key technologies.

Realization of reconfigurable super-resolution imaging by liquid microlens arrays integrated on light disk

The microlens-assisted microscope realizes super-resolution imaging and observation, and has the advantages of no marking, no damage, real-time, localization, and good environmental compatibility. Liquid microlens arrays with uniformity and easy manipulation can realize super-resolution imaging without complicated mechanical scanning and driving. However, simply and efficiently controlling the imaging distance is a key technical challenge to the realization of super-resolution imaging of microlens. In this paper, the uniform depths of photoresist microholes on light disk are fabricated by ultraviolet exposure technology. Using liquid self-assembly technology, the microholes are filled with glycerol droplets, and thus ensuring the near-field imaging distance of the microlens. The reconfigurable super-resolution of 226-nm-wide grating line and the imaging magnification of 1.59 times are observed under the optical microscope. At present, the theory of super-resolution imaging based on microlens is not unified and perfect. In this paper, the Abbe imaging principle is used to explain the imaging magnification and super-resolution characteristics. Therefore, the liquid microlens arrays integrated on the light disk show great potential application in optical nanometer measurements and sensing devices.

A Fast Detection Method Using Anisotropic Guidance for Infrared Small Target Under Complex Scenes

The development of intelligent control and visual navigation, along with the ongoing increase in imaging distance, has led to realistic demands for weak and small target detection. However, figuring out how to reduce the interference of various complex factors while achieving a high detection rate and low false alarm rate for real-time infrared small target detection is still a significant challenge. We propose a computationally simple single-frame infrared small target fast detection method applicable to complex scenes. First, a novel anisotropy filter bank suitable for small target feature extraction is constructed and modified with a point spread function. This makes it possible to map the salient features and spatial features of the target in the spatial domain using the imaging mechanism. We then combined two sets of feature parameters using the filtered features, including isotropy measure and directional energy factors, to enable the detection of small targets. Experimental findings showed that the algorithm performs well in scenarios involving complicated clouds, urban ground, and vegetation. The software also achieved excellent real-time performance because of its straightforward computational design.

Topographic Mapping Capability Analysis of Moderate Resolution Imaging Camera (MoRIC) Imagery of Tianwen-1 Mars Mission

The Moderate Resolution Imaging Camera (MoRIC) onboard the orbiter of China’s Tianwen-1 Mars mission aims to map the surface of Mars globally and to explore its topography and geomorphology. This camera’s wide field of view can be used to overlap adjacent images sufficiently for topographic reconstruction. This study aimed to assess the topographic mapping potential of MoRIC images via a systematic accuracy analysis of MoRIC stereo mapping based on theoretical calculation and experimental validation. Experimental analyses were conducted using digital elevation models (DEMs) based on MoRIC images covering the Zhurong rover landing area and Mars Chart 11 region. Comparisons between these DEMs and reference DEMs revealed that the elevation accuracy of the former was approximately one ground sampling distance of the MoRIC image, which is consistent with the theoretical accuracy. Based on these results, MoRIC can be used to effectively map the Martian surface via stereo photogrammetry. These results serve as a useful guideline for topographic mapping based on MoRIC images and their application in various streams of research.

Demonstration kits for locating an image formed by a concave mirror

To improve student understanding about an image formed by a concave mirror, 2 demonstration kits were developed. One kit is used to view and locate images formed and find the image distances and sizes. The other uses a laser beam to show the incident and reflected light rays and relate to the ray diagram normally used to find the image location. The demonstration kits were applied to year-11 Thai high-school students for both online (N = 32) and on-site (N = 22) classes. The 4 diagnostic questions were used to investigate student understanding, covering the image visualization, the mirror equation, and the ray diagrams of a concave mirror. The mean scores of the pre- and post-test are 1.3 and 5.3 out of 13, respectively, and the averaged normalized gain is 0.34. Interestingly, the normalized gains of the two classes are not significantly different indicating that the demonstration kits can be applied to either an online or on-site class. The best improvement was found in the image visualization question. In addition, the demonstration kits make the physics content enjoyable. The students found it exciting and fun while much is being learned.

Automatic Number Extraction from Fixed Imaging Distance

Developed countries are facing many challenges to convert large areas of existing services to electronic modes, reflecting the current nature of workflow and the equipment utilized for achieving such services. For instance, electricity bill collection still tend to be based on traditional approaches (paper-based and relying on human interaction) making them comparatively time-consuming and prone to human error. This research aims to recognize numbers in mechanical electricity meters and convert them to digital figures utilizing Optical Character Recognition (OCR) in Matlab. The research utilized the location of red region in color electricity meters image to determine the crop region that contain the meters numbers, then extracts this numbers region and convert it into binary image and extract the numbers as a text using OCR technique. A camera for the Iphone 6 (8-megapixel) is used to take a snapshot of the meter screen. The red box in the meter is used to calculate the window coordinates (vertical and horizontal length) that contain the numbers in the original image. The results show a high level of accuracy, reaching 100% due to the effort done on pre-processing the digital images before feeding the part that contains the numbers into the OCR engine. Compared to the maximum accuracy obtained in other previous research of less than 100% in most of related works, the suggested method provide better approach to obtain the optimum results . Despite the strong results, some challenges still need to be investigated further to find the best solutions, for example the issue of scratched or unclear meter screen, also the meter type 2 (the type that do not have the red box)

Shielding Adequacy of Conventional X-ray Facilities in Kano Metropolis, Nigeria using RadShield Software

Over time x-ray department gains more patient throughput compared to when it was established, this may lead to changes in room usage, workload and occupancy factor. Therefore, it becomes imperative to re-evaluate the shielding adequacy of the facilities to ensure the appropriate shielding design goal is accomplished. The study was aimed at assessing the shielding adequacy of conventional x-ray rooms in ten radio diagnostic centres in Kano Metropolis using RADSHIELD software. This was a prospective, cross-sectional study. RadShield software version 1.1 was used in the study, parameters such as distances of each wall from a radiation source (D), the average number of patients per week (N), occupancy factor (T), and use factor (U) were inserted into the software together with the shielding design goal (P). Once the result was generated, the design and shielding variables were saved in .xml format. The data were analyzed using Excel 2016. Ten facilities were studied involving 14 x-ray rooms. Room III had the largest room size of 49.2 m2 while room X had the least room size of 12.8 m2. Room II had the longest source image distance (SOD) of 180cm while room IV had the shortest (120cm). The design barrier thickness was thickest (47 cm) in room II and thinnest (1.5 cm) in barrier 5 of room III. All the x-ray rooms had the ideal room size except facilities G and H. The design barrier thickness in the radiology department of all the conventional x-ray rooms involved in the study was adequate.

Circular array transducer based-photoacoustic/ultrasonic endoscopic imaging with tunable ring-beam excitation

Photoacoustic/ultrasound endoscopic imaging is regarded as an effective method to achieve accurate detection of intestinal disease by offering both the functional and structural information, simultaneously. Compared to the conventional endoscopy with single transducer and laser spot for signal detection and optical excitation, photoacoustic/ultrasound endoscopic probe using circular array transducer and ring-shaped laser beam avoids the instability brought by the mechanical scanning point-to-point, offering the dual-modality imaging with high accuracy and efficiency. Meanwhile, considering the complex morphological environments of intestinal tracts in clinics, developing the probe having sufficient wide imaging distance range is especially important. In this work, we develop a compact circular photoacoustic/ultrasonic endoscopic probe, using the group of fiber, lens and home-made axicon, to generate relatively concentrated ring-shaped laser beam for 360° excitation with high efficiency. Furthermore, the laser ring size can be tuned conveniently by changing the fiber-lens distance to ensure the potential applicability of the probe in various and complex morphological environments of intestines. Phantom experimental results demonstrate imaging distance range wide enough to cover from 12 mm to 30 mm. In addition, the accessibility of the photoacoustic signals of molecular probes in ex vivo experiments at the tissue depth of 7 mm using excitation energy of 5 mJ has also been demonstrated, showing a high optical excitation efficiency of the probe.

Real-time, multi-spectral motion artefact correction and compensation for laser speckle contrast imaging

Laser speckle contrast imaging (LSCI) is so sensitive to motion that it can measure the movement of red blood cells. However, this extreme sensitivity to motion is also its pitfall as the clinical translation of LSCI is slowed down due to the inability to deal with motion artefacts. In this paper we study the effectiveness of a real-time, multi-spectral motion artefact correction and compensation by subduing an in vitro flow phantom and ex vivo porcine kidney to computer-controlled motion artefacts. On the in vitro flow phantom, the optical flow showed a good correlation with the total movement. This model results in a better signal-to-noise ratios for multiple imaging distances and the overestimation of perfusion was reduced. In the ex vivo kidney model, the perfusion overestimation was also reduced and we were still able to distinguish between ischemia and non-ischemia in the stabilized data whereas this was not possible in the non-stabilized data. This leads to a notably better perfusion estimation that could open the door to a multitude of new clinical applications for LSCI.

Classification and visual explanation for COVID-19 pneumonia from CT images using triple learning

This study presents a novel framework for classifying and visualizing pneumonia induced by COVID-19 from CT images. Although many image classification methods using deep learning have been proposed, in the case of medical image fields, standard classification methods are unable to be used in some cases because the medical images that belong to the same category vary depending on the progression of the symptoms and the size of the inflamed area. In addition, it is essential that the models used be transparent and explainable, allowing health care providers to trust the models and avoid mistakes. In this study, we propose a classification method using contrastive learning and an attention mechanism. Contrastive learning is able to close the distance for images of the same category and generate a better feature space for classification. An attention mechanism is able to emphasize an important area in the image and visualize the location related to classification. Through experiments conducted on two-types of classification using a three-fold cross validation, we confirmed that the classification accuracy was significantly improved; in addition, a detailed visual explanation was achieved comparison with conventional methods.

The Dahu graph-cut for interactive segmentation on 2D/3D images

Interactive image segmentation is an important application in computer vision for selecting objects of interest in images. Several interactive segmentation methods are based on distance transform algorithms. However, the most known distance transform, geodesic distance, is sensitive to noise in the image and to seed placement. Recently, the Dahu pseudo-distance, a continuous version of the minimum barrier distance (MBD), is proved to be more powerful than the geodesic distance in noisy and blurred images. This paper presents a method for combining the Dahu pseudo-distance with edge information in a graph-cut optimization framework and leveraging each’s complementary strengths. Our method works efficiently on both 2D/3D images and videos. Results show that our method achieves better performance than other distance-based and graph-cut methods, thereby reducing the user’s efforts.

Bifacial-metasurface-enabled pancake metalens with polarized space folding

Replacing traditional refractive lenses with metalenses that have ultrathin and flat architecture could make imaging systems more compact. However, the space between the lens and image is usually the dominating factor in determining the bulkiness, and it cannot be shortened just by using thinner lenses. Here, we propose a pancake metalens that folds the optical path at will using a metacavity consisting of a spin-dependent bifacial metasurface and a mirror. We first verify the asymmetric and independent functions of this bifacial metasurface, and then demonstrate the polarized space-folding effect of the metacavity. Imparted with specifically designed phase, we demonstrate a pancake metalens with on-demand (e.g., 2/3 and 4/5) reduction of imaging distance and relatively good imaging performance. This pancake metaoptics framework could enable miniaturization of imaging systems and would provide insights for metadevice applications.

Determining the Focal Length of Converging and Diverging Lenses Using a Smartphone

In this study, we propose a novel and direct method of determining the focal length of a converging or diverging lens using a smartphone. The standard optical sensor used in modern smartphone cameras is an active-pixel sensor called the complementary metal–oxide–semiconductor (CMOS). The CMOS is covered by an assembly of five to seven camera lenses that can be moved along the axis of the camera to electronically adjust its overall effective focal length, i.e., the autofocus feature. This collection of lenses, referred to as a system of adaptive optical lenses, can be treated as a single effective converging lens that forms a real image on the CMOS sensor array. We assume that the image distance between the CMOS sensor array and the smartphone camera lens (SCL) is a constant. Based on this assumption, a two-step procedure is proposed to accurately obtain the focal length of a lens without the need for additional lenses.

HCFN: Hierarchical cross-modal shared feature network for visible-infrared person re-identification

Compared with traditional visible–visible person re-identification, the modality discrepancy between visible and infrared images makes person re-identification more challenging. Existing methods rely on learning efficient transformation mechanisms in paired images to reduce the modality gap, which inevitably introduces noise. To get rid of these limitations, we propose a Hierarchical Cross-modal shared Feature Network (HCFN) to mine modality-shared and modality-specific information. Since infrared images lack color and other information, we construct an Intra-modal Feature Extraction Module (IFEM) to learn the content information and reduce the difference between visible and infrared images. In order to reduce the heterogeneous division, we apply a Cross-modal Graph Interaction Module (CGIM) to align and narrow the set-level distance of the inter-modal images. By jointly learning two modules, our method can achieve 66.44% Rank-1 on SYSU-MM01 dataset and 74.81% Rank-1 on RegDB datasets, respectively, which is superior compared with the state-of-the-art methods. In addition, ablation experiments demonstrate that HCFN is at least 4.9% better than the baseline network.

Clinical and Neuroimaging Profile of Neonates With Moderate-to-Severe Encephalopathy Treated With Therapeutic Hypothermia

Objective: To demonstrate the clinical and neuroimaging profile of infants with moderate-to-severe encephalopathy after therapeutic hypothermia (TH) in the Indian setting. The secondary objective was to determine the logistics involved in performing neuroimaging in these infants. Design and Setting: A retrospective descriptive study in 2 tertiary centers. Methods: All infants who underwent cooling in both centers from January 2019 to December 2019 were included. Demographic data, details of cooling, clinical and neuroimaging profile (magnetic resonance imaging [MRI] and magnetic resonance spectroscopy [MRS]), and details of the logistics involved in performing the imaging (sedation, neonatal transport, personnel, distance traveled, and time taken) were collected and analyzed. Results: A total of 44 infants were enrolled of which 37 (84.0%) underwent both TH and neuroimaging (MRI and MRS). A total of 33 (75.0%) of infants were outborn, 20 (45.5%) of them had sentinel events before delivery and 17 (38.6%) were intubated at birth. Apgar score <5 min was seen in 8 (18.2%) and seizures in 23 (52.3%) of infants. A total of 37 (84.1%) survived until discharge and underwent neuroimaging. Neuroimaging was performed between 5 and 14 days after birth. The most common abnormal finding on MRI brain was the signal changes in watershed areas of brain 8 (18.2%) and on MRS was low N-acetyl aspartate and high lactate 13 (29.5%). Midazolam (68.2%) and Triclofos (15.2%) were the sedatives used during neuroimaging these infants. Conclusion: TH for infants with neonatal encephalopathy resulted in excellent survival outcomes in tertiary private sector hospitals.

Accurate measurement of virtual image distance for near-eye displays based on auto-focusing.

Virtual reality (VR) and augmented reality (AR) are able to project virtual images to human eyes at a certain depth distance. This virtual image distance can be adjusted by controlling the diopter of the near-eye display. However, it is difficult to measure accurately and continuously since this virtual image distance spans a large range. In this work, we propose a method to accurately determine the virtual image distance of commercial VR/AR equipment. The measurement apparatus is built and calibrated to validate the feasibility. The focal distance of the focus-tunable lens can be automatically adjusted via a step motor by cooperating with the image sharpness analyzing program. Compared with other proposed methods, ours provides an effective means to achieve high accuracy, a wide and continuous testing range, and automatic evaluation of virtual image distance for compact near-eye displays.

Ultra-Wideband Frequency Modulated Continuous Wave Photonic Radar System for Three-Dimensional Terahertz Synthetic Aperture Radar Imaging

Three-dimensional (3D) imaging remains an expensive and challenging task in the THz band. In this study, a frequency-modulated continuous-wave photonic radar system was presented in the 300-GHz band, instead of using electronic-based devices. The proposed system can obtain a 6-dB bandwidth of 120 GHz to achieve a range resolution of ∼1.1 mm. The frequency sweep linearity of a laser source was calibrated with respect to the imaging distance and range resolution, through which a maximum detectable distance of ∼800 mm was achieved with the collimated beam. To obtain the desired 3D information, the synthetic aperture radar (SAR) technique was introduced to the proposed system to achieve 3D imaging, which was not bounded by the fixed focal distance of a focus lens. It can provide a spatial resolution of ∼1.5 mm within a 3D imaging range up to ∼300 mm. The potential and limitations of SAR imaging schemes are discussed based on the theoretical and experimental results.

Seeing destinations through short-form videos: Implications for leveraging audience involvement to increase travel intention

Short-form travel videos are popular, but the process of audience involvement while watching remains unclear. This study explores audience involvement along with expressions of travel intention and introduces the concepts of destination image and psychological distance to construct a structural model. A total of 487 questionnaires were used for structural equation model testing. Results show that audience involvement has a positive impact on the destination’s cognitive and affective image, ultimately leading to travel intention. Meanwhile, the destination’s cognitive and affective image play a partial mediating role between the influencing mechanisms. Moreover, psychological distance has a negative moderating effect between audience involvement and travel intention, and on audience involvement and cognitive image. However, it has no significant moderating effect on both audience involvement and affective image. The results provide a broader research perspective for the development of short-form travel videos and provide important implications for destination marketing.

AUTOMATIC DETECTION AND DIMENSIONAL MEASUREMENT OF MINOR CONCRETE CRACKS WITH CONVOLUTIONAL NEURAL NETWORK

Abstract. The increasing number of aging infrastructures has drawn attention among the industry as the results caused by critical infrastructure failure could be destructive. It is essential to monitor the infrastructure assets and provide timely maintenance. However, one of the crucial problems is that the budget allocated to the maintenance stage is much less than that for the designing and construction stages. The cost of labor, equipment, and vehicles are significant. Therefore, it is impossible to perform a thorough inspection by human inspectors over each asset. A more efficient method will be needed to solve this problem. This paper aims to provide an automatic approach to detecting and measuring the dimensions of minor cracks that appear on concrete structures with a noisy background. This research also investigates the relationship between image pixel size, accuracy, detection rate of cracks, and shooting distance of images. The proposed method will be able to reduce the cost and increase accuracy. A case study was performed on a concrete sewer with cracks distributed on the surface in Sydney, New South Wales, Australia.

Optics of the metalens

A metalens is an ultra-thin lens made of a metasurface, with focusing and imaging functions, and with promising applications in miniature optical systems, such as mobile devices. This paper gives an introduction to the optics of metalenses. First, we examine the focusing and imaging characteristics of metalenses. And then, as an essential step, we derive the refraction law of metasurfaces from the Huygens’s principle. It is then that some basic formulas of the metalens, for focusing and imaging, are derived at a level appropriate for undergraduate students. We begin with the derivation of the phase profile of a metalens. Then we derive the lens equation of the metalens, which relates the object and image distance in a metalens. The paper closes with a discussion of the relationship between the metalens and the classical refractive lens.