Different Fields Of View Research Articles

Distributed Multi-Sensor Fusion for Multi-Group/Extended Target Tracking with Different Limited Fields of View

The identification of sensing group targets and extended targets is of paramount importance in the context of vehicle tracking and early warning detection. As the scope of target monitoring and tracking extends, conventional single-sensor-based tracking techniques are proving to be inadequate in meeting the practical demands of the field. Consequently, multi-sensor fusion tracking technology has emerged as a viable alternative. However, the use of multiple sensors is constrained by their limited fields of view (FOVs), which leads to issues such as the loss of target detection and the introduction of false targets after fusion. Hence, this study proposes a combination of weighted geometric averaging (WGA) and weighted arithmetic averaging (WAA) methods to solve distributed multi-group/extended target tracking with different fields of view. Specifically, a local Poisson multi-Bernoulli mixture (PMBM) filter was first used on individual sensors. Subsequently, we combined a sequential fusion technique and the proposed fusion approach to fuse the PMBM filter densities. The efficacy and superiority of this approach were demonstrated through simulations.

Effects of Different Fields of View and Rotation Angles on Radiation Doses to Highly Radiosensitive Organs in Children Using Dental Cone Beam Computed Tomography

Dental cone beam computed tomography (CBCT) is a diverse 3D X-ray imaging technique that has enabled clear visualization of the teeth and surrounding structures. The most common diagnostic purpose of dental CBCT examination in children is ectopic eruption and impacted teeth, and a small field of view (FOV) is often used. Since it is difficult for children to control their body movements, reducing the rotation angle is effective. However, no studies have examined the effects of different rotation angles on radiation doses to highly radiosensitive organs in children using small FOVs. The purpose of this study was to examine the effects of small FOVs (4 × 4 cm and 6 × 6 cm) and rotation angles (360° and 180°) on doses that highly sensitize organs in children using dental CBCT. The entrance surface doses to lenses, thyroid lobes, parotid glands, and sublingual glands of a pediatric whole-body phantom were measured. By reducing the FOV from 6 × 6 cm to 4 × 4 cm, the dose to the sublingual gland could be significantly decreased. Additionally, by reducing the rotation angle from 360° to 180°, the lens dose can be decreased significantly. As the rate of dose reduction varies among organs, it is important to consider the relative positions of different organs with respect to the FOV and the trajectory of the X-ray tube.

Semi-analytical Monte Carlo simulation of underwater target echoes from a small UAV-based oceanic lidar

Small unmanned airborne oceanic lidars are becoming increasingly popular for ocean surveys. They typically weigh less than 10 kg and can be mounted on commonly used commercial drones, making them easier to use than traditional large oceanic lidars, which typically weigh up to 80 kg and can only be carried on manned aircraft. Unmanned airborne oceanic lidars typically fly at lower altitudes and use higher laser emission frequencies, making them suitable for detecting underwater targets. However, most of the existing LiDAR underwater echo simulation models are designed for flat terrain and assume that the target fills the LiDAR receiving field of view, and there are few studies on the echoes of suspended targets smaller than the field of view range. Therefore, we combined ray tracing and semi-analytical Monte Carlo to model the laser echo energy of the underwater target. The study investigated the energy change of the target echo in the direction of deviation from the laser outgoing direction, and the impact of absorption and scattering coefficients on it. The difference in echo energy between different fields of view for extended and non-extended targets and the effect of water quality on it were explored. The echo waveforms of the target under different tilt angles were simulated, and it was found that the target echo pattern will be tilted with the change of tilt angle and offset position.

Orthonormal aberration decomposition for circular aperture and rectangular field with extension to multiple-aperture systems

A new set of orthogonal polynomials and the traditional Zernike polynomials are combined to construct the wavefront of the sparse aperture (SA) optical system. The new set of orthogonal polynomials in the rectangular domain is derived based on the Zernike polynomials. The modulation transfer functions (MTFs) of the SA system under different fields of view are calculated. The effects of some wavefront terms on the field-related MTF are analyzed. Imaging simulation and restoration are conducted for the SA system. The results indicate that the wavefront of the SA system can be represented by the combination of the new set of orthogonal polynomials and the Zernike polynomials. The former represents the field term, and the latter represents the pupil term of the wavefront. The field-related Wiener filter is constructed to restore the imaging results of the SA system, and the results show that the image quality can be improved greatly through restoration.

TEM-processed defect densities in single-layer TMDCs and their substrate-dependent signature in PL and Raman spectroscopy

The optical properties of the direct-bandgap transition metal dichalcogenides (TMDCs) MoS2 and WS2 are heavily influenced by their atomic defect structure and substrate interaction. In this work we use low-voltage chromatic and spherical aberration (CC/CS)-corrected high-resolution transmission electron microscopy to simultaneously create and image chalcogen vacancies in TMDCs. However, correlating the defect structure, produced and analyzed using transmission electron microscopy (TEM), with optical spectroscopy often presents challenges because of very different fields of view and sample platforms involved. Here we employ a reverse transfer technique to transfer electron-irradiated single-layer MoS2 and WS2 from the TEM grid to various substrates for subsequent optical examination. The dynamics of defect creation are studied in atomic resolution on a separate sample, which allows to apply the derived statistics to larger irradiated areas on the other samples. The intensity of both the defect-bound exciton peak in photoluminescence (PL) and the defect-induced LA(M) mode in Raman spectra increase with defect density. The best substrates for defect-density determination by optical spectroscopy are polystyrene for PL and SiC and Si/SiO2 for Raman spectroscopy. These investigations represent an important step towards the quantification of defects using solely optical spectroscopy, paving the way for fast, reliable, and automatable optical quality control of optoelectronic devices.

Assessing Genotoxicity and Cytotoxicity Induced by X-Ray Exposure From Cone Beam Computed Tomography at Varied Fields of View.

The practice of dentistry benefits greatly from cone beam computed tomography (CBCT) and advantages should be prioritized over hazards; even modest doses of X-rays have the potential to have cytotoxic effects, damage DNAthrough their clastogenic impact, and stimulate the creation of micronucleialong with further nuclear changes. To assess the genotoxicity and cytotoxicity of X-rays in exfoliated oral mucosal cells from patients who underwent CBCTscans at different fields of view (FOV), and to examine and assess the extent of cytotoxicity and genotoxicity caused by X-rays in oral exfoliated cells of people who were subjected to CBCT at different fields of view (FOV). Following CBCT exposure, 66 patients were chosen from the Department of Oral Medicine and Radiology at the SVS Institute of Dental Sciences, Mahbubnagar. Cells from the buccal mucosa were then extracted using the exfoliative cytology method, and the samples were examined under a microscope to look for nuclear and cytological abnormalities. A paired t-test analysis revealed that mean micronuclei increased significantly in each study group from before to after exposure. It increased in Group I from 93.59 to 96.05, in Group II from 83.27 to 91.86, and in Group III from 86.05 to 97.00. Various test analyses revealed an important relation between exposure status and the presence of karyorrhexis in Group III. There was no association in other groups. The study revealed a significant increase of micronuclei in subjects after exposure to radiation at various FOVs.There was an increased karyorrhexis following radiation exposure in all groups at various FOVs. The significant association between exposure and karyorrhexis in the larger size FOV group was noticed further potentiating the extent of increased damage as the size of FOV is increased.

Sources of Variability in Determinations of Brewing Yeast Total Cell Counts and Viability Obtained by Microscopy

Brewers utilizing yeast cell counts and determinations of yeast viability obtained by microscopy require precise results for calculating the yeast pitch to produce fermentations with the highest quality and consistency. The steps in obtaining results with the desired precision include identifying, quantifying and controlling the sources of variation. In this study, we used simulated cell counting, manual cell counting, and semi-automated cell counting to explore sources of variation contributing to the variability of yeast cell counts and yeast viability determinations. The results showed that the variability associated with counting different fields of view contributed most to the variability in yeast cell counts and determinations of yeast viability. Understanding the sources and amounts of variation in cell counts will help brewers direct their efforts toward obtaining the highest quality determinations of yeast cell counts and viability.

Optimization of orofacial cleft imaging protocols using device-specific low-dose cone-beam computed tomography.

The aim of this study was to present optimized device-specific low-dose cone-beam computed tomography (CBCT) protocols with sufficient image quality for pre-surgical diagnostics and three-dimensional (3D) modelling of cleft defects. Six paediatric skulls were acquired, and an artificial bony cleft was created. A high-resolution CBCT scan acted as a reference standard (Accuitomo 170, Morita, Kyoto, Japan) for comparing eight low-dose protocols of Newtom VGi-evo (QR Verona, Cefla, Verona, Italy), which included Eco and Regular protocols with different field of views (FOVs). Delineation of lamina dura, cementoenamel junction (CEJ), trabecular bone and bony bridge were assessed. A 3D model of the defect was also evaluated. The dose area product of low-dose protocols ranged from 31 to 254 mGy*cm2. Despite the dose difference of up to eight times between applied protocols, trabecular bone and CEJ exhibited appropriate image quality in all scans. However, Regular small FOV protocols (5 × 5 and 8 × 5 cm2), for both lamina dura and bony bridge, demonstrated a significant improvement in image quality compared to Eco FOV counterparts. Based on 3D defect analysis, no significant difference existed between low-dose protocols and the reference standard. The findings highlight the possibility of achieving a considerable reduction (up to eight times) in the radiation dose using low-dose CBCT protocols while maintaining sufficient image quality for assessing anatomical structures and 3D modelling in cleft cases.

High dynamic range spatial heterodyne one-dimensional imaging spectroscopy based on a digital micromirror device.

Spatial heterodyne one-dimensional imaging spectrometer (SHIS) can simultaneously acquire hyperspectral information from different fields of view (FOVs). However, the dynamic range of SHIS is limited by the detector's performance. We propose a high dynamic range spatial heterodyne one-dimensional imaging spectroscopy (HD-SHIS) based on a digital micromirror device (DMD), which can control the exposure time of each FOV signal by adjusting the flip time of micromirrors on an M-bit DMD, realizing the simultaneous detection of strong and weak signals in FOVs with a theoretical improvement of the dynamic range by dB. Meanwhile, HD-SHIS utilizes a DMD to realize the Hadamard modulation of interference data in the spectral dimension, which can be used with the linear array detector to complete the detection of the imaging spectrum. We have built an HD-SHIS principle prototype and carried out dynamic range experiments. The experimental results show that HD-SHIS can achieve 48 dB dynamic range improvement by utilizing an 8-bit display width DMD.

Convolutional Cross-View Pose Estimation.

We propose a novel end-to-end method for cross-view pose estimation. Given a ground-level query image and an aerial image that covers the query's local neighborhood, the 3 Degrees-of-Freedom camera pose of the query is estimated by matching its image descriptor to descriptors of local regions within the aerial image. The orientation-aware descriptors are obtained by using a translationally equivariant convolutional ground image encoder and contrastive learning. The Localization Decoder produces a dense probability distribution in a coarse-to-fine manner with a novel Localization Matching Upsampling module. A smaller Orientation Decoder produces a vector field to condition the orientation estimate on the localization. Our method is validated on the VIGOR and KITTI datasets, where it surpasses the state-of-the-art baseline by 72% and 36% in median localization error for comparable orientation estimation accuracy. The predicted probability distribution can represent localization ambiguity, and enables rejecting possible erroneous predictions. Without re-training, the model can infer on ground images with different field of views and utilize orientation priors if available. On the Oxford RobotCar dataset, our method can reliably estimate the ego-vehicle's pose over time, achieving a median localization error under 1 m and a median orientation error of around 1 ° at 14 FPS.

Impact of acquisition volume on cone beam computed tomography imaging of marginal bone: an ex vivo study.

The current study explores whether there is a clinically relevant distinction in the measurement of marginal bone loss when comparing high-dose (HD) versus low-dose (LD) cone beam computed tomography (CBCT) protocols in small and large acquisition volumes. Material and Methods: CBCTs of four human cadaveric preparates were taken in HD and LD mode in two different fields of view 8 × 8 cm2 (LV) and 5 × 5 cm2 (SV). In total, 43 sites of 15 teeth were randomly chosen, and marginal bone loss was measured twice in all protocols at 43 sites of 15 teeth by one calibrated investigator. Bland-Altman plots and Lin's concordance correlation coefficient (CCC) were calculated to assess the extent of agreement of the measurements. Additionally, the rater scored the certainty in each of the measurements. For HD-CBCT CCC of measurements obtained using SV versus LV was 0.991. CCC of measurements obtained using SV versus LV of LD-CBCT was 0.963. Both CCC values indicated excellent agreement between the two volumes in both protocols. CCC also indicated high intramodality correlation between HD-CBCT and LD-CBCT independent of the acquisition volume (0.963 - 0.992). Bland-Altman plots also indicated no substantial differences. Results of certainty scoring showed significant differences (p = 0.004 (LV), p < 0.001(SV)) between the LD and HD-CBCT. Accuracy of measurements of bone loss shows no clinical noticeable effects depending on the CBCT volume in this ex vivo study. There appears to be no relevant advantage of SV over LV, neither in HD-CBCT nor in LD-CBCT and additionally no relevant advantage of HD versus LD in visualizing marginal bone loss.

Megahertz multi-parametric ophthalmic OCT system for whole eye imaging

An ultrahigh-speed, wide-field OCT system for the imaging of anterior, posterior, and ocular biometers is crucial for obtaining comprehensive ocular parameters and quantifying ocular pathology size. Here, we demonstrate a multi-parametric ophthalmic OCT system with a speed of up to 1 MHz for wide-field imaging of the retina and 50 kHz for anterior chamber and ocular biometric measurement. A spectrum correction algorithm is proposed to ensure the accurate pairing of adjacent A-lines and elevate the A-scan speed from 500 kHz to 1 MHz for retinal imaging. A registration method employing position feedback signals was introduced, reducing pixel offsets between forward and reverse galvanometer scanning by 2.3 times. Experimental validation on glass sheets and the human eye confirms feasibility and efficacy. Meanwhile, we propose a revised formula to determine the “true” fundus size using all-axial length parameters from different fields of view. The efficient algorithms and compact design enhance system compatibility with clinical requirements, showing promise for widespread commercialization.

HeLiPR: Heterogeneous LiDAR dataset for inter-LiDAR place recognition under spatiotemporal variations

Place recognition is crucial for robot localization and loop closure in simultaneous localization and mapping (SLAM). Light Detection and Ranging (LiDAR), known for its robust sensing capabilities and measurement consistency even in varying illumination conditions, has become pivotal in various fields, surpassing traditional imaging sensors in certain applications. Among various types of LiDAR, spinning LiDARs are widely used, while non-repetitive scanning patterns have recently been utilized in robotics applications. Some LiDARs provide additional measurements such as reflectivity, Near Infrared (NIR), and velocity from Frequency modulated continuous wave (FMCW) LiDARs. Despite these advances, there is a lack of comprehensive datasets reflecting the broad spectrum of LiDAR configurations for place recognition. To tackle this issue, our paper proposes the HeLiPR dataset, curated especially for place recognition with heterogeneous LiDARs, embodying spatiotemporal variations. To the best of our knowledge, the HeLiPR dataset is the first heterogeneous LiDAR dataset supporting inter-LiDAR place recognition with both non-repetitive and spinning LiDARs, accommodating different field of view (FOV)s and varying numbers of rays. The dataset covers diverse environments, from urban cityscapes to high-dynamic freeways, over a month, enhancing adaptability and robustness across scenarios. Notably, HeLiPR dataset includes trajectories parallel to MulRan sequences, making it valuable for research in heterogeneous LiDAR place recognition and long-term studies. The dataset is accessible at https://sites.google.com/view/heliprdataset.

Stochastic Outlier Selection via GM-CPHD Fusion for Multitarget Tracking Using Sensors With Different Fields of View

Stochastic Outlier Selection via GM-CPHD Fusion for Multitarget Tracking Using Sensors With Different Fields of View

A high resolution prism-grating panoramic imaging spectrometer based on occultation observations

Occultation observation is an important technique for shadow region detection and a significant complement to the illuminated region detection method. This technology will significantly reduce the impact of background light pollution and provide clearer occultation signals. In order to achieve high-resolution all-round detection in the shadow region, this paper introduces a proposal for a prism-grating panoramic imaging spectrometer based on occultation observations. It utilizes a panoramic annular lens to enable 360-degree occultation observations within the shadow region, combines a grating for spectral separation to obtain spectral information, and achieves an overall straight-line design for the system by adjusting the prism-grating surface's deflection angle. This paper, by analyzing the non-uniformity of light rays from different fields of view after dispersion by the grating, obtains the coordinate information of the spectrum on the image plane, significantly improving the accuracy of subsequent spectral calibration. The design results indicate that the optical system of this imaging spectrometer achieves a spectral resolution of 0.67 nm in the wavelength range of 365–770 nm. At a Nyquist frequency of 37.04lp/mm, the MTF across the entire bandwidth exceeds 0.6. The RMS of the point spread function is less than 9 μm across the full field of view, and aberration correction is excellent. This imaging spectrometer utilizes stellar occultations to achieve real-time 360-degree observations in the shadow region, and at the same time obtains total information on atmospheric components and contour information that varies with occultation height. This scheme offers a more comprehensive information for scientists in related fields.

Extended scene deep-phase-retrieval Shack-Hartmann wavefront sensors

Context. Strong atmospheric turbulence has been a challenge for high-resolution imaging of solar telescopes. Adaptive optics (AO) systems are capable of improving the quality of imaging by correcting partial aberrations. Thus, the performance of Shack-Hartmann sensors in measuring aberrations generally determines the upper performance bound of AO systems. In solar AO, classic correlation Shack-Hartmann sensors only correct a small number of modal aberrations. Moreover, strong aberrations are difficult to measure stably by correlation Shack-Hartmann. In this context, the improvement in the performance of Shark-Hartmann sensors promises to enable higher-resolution imaging of extended objects for ground-based telescopes or Earth observation. Aims. We propose a new extended scene deep-phase-retrieval Shack-Hartmann wavefront sensing approach to improve the image quality of solar telescopes. It is capable of achieving high-accuracy measurements of high-spatial-resolution wavefronts on extended scene wavefront sensing. Moreover, it has great generalization when observing unknown objects from different fields of view of the telescope. Methods. Our proposed approach can extract features resembling the sub-aperture point spread function (PSF) from a Shack-Hartmann sensor image without any prior information. Then a convolutional neural network is used to establish a nonlinear mapping between the feature image and the wavefront modal coefficients. The extracted feature greatly eliminates the shape information of the extended object while maintaining more information related to aberrations. We verified the performance of the proposed method through simulations and experiments. Results. In the indoor experiment on the ground layer adaptive optics (GLAO) of the 1 m New Vacuum Solar Telescope, compared to the Shack-Hartmann correlation method, the proposed method reduces the correction errors by more than one third. When observing objects from different fields of view in the GLAO that differ from the object in the training data, the relative errors fluctuate within the range of 20% to 26%. The AO system with the proposed wavefront measurement method can obtain higher-resolution focal images of the simulated solar granulation after a round of offline correction. The average latency of the proposed method is about 0.6 ms.

The Accuracy of Guided Implant Surgery With Different Fields of View of Cone-Beam Computerized Tomography.

Although a smaller size field of view (FOV) of cone-beam computerized tomography (CBCT) reduces radiation exposure, its effect on the accuracy of static computer-aided implant surgery (s-CAIS) remains unknown. This study aimed to evaluate the impact of the size of FOV on the accuracy of s-CAIS and to investigate if the arch affects this effect. A total of 32 implant sites on 8 identical scannable models (maxillae and mandibles) were randomly allocated to 2 FOV sizes: test (5 × 5 cm) and control (10 × 10 cm). All models were scanned with an intraoral scanner (IOS). With the registration of the surface scan and CBCT image, a prosthetic-driven implant position was planned. Following the fabrication of surgical templates, a single-blinded surgeon placed all implants with the fully guided s-CAIS protocol. IOS captured the implant positions with the scan body attached. Implant-planning software measured the angular deviation, 3-dimensional (3D) deviation at the crest, and 3D deviation at the apex between preplanned and actual implant positions. Two-way analysis of variance was used to analyze the effect of FOV and arch on the deviations. The size of FOV did not show a significant effect (P > .198) on angular deviation, 3D deviation at the crest, or 3D deviation at the apex. No significant difference was found when comparing the effect of the size of FOV between the maxillary and mandibular implants. In conclusion, the use of small FOV CBCT demonstrated comparable accuracy of s-CAIS to the use of medium FOV CBCT.

The Langley ratio method, a new approach for transferring photometer calibration from direct sun measurements

Abstract. This article presents a new method for transferring calibration from a reference sun photometer, referred to as the “master”, to a secondary sun photometer, referred to as the “field”, using a synergetic approach when master and field instruments have different spectral bands. The method was first applied between a precision filter radiometer (denoted PFR) instrument from the World Optical Depth Research and Calibration Center (WORCC), considered the reference by the WMO (World Meteorological Organization), and a CE318-TS photometer (denoted Cimel), the standard photometer used by AERONET (AErosol RObotic NETwork). These two photometers have different optics, sun-tracking systems, and spectral bands. The Langley ratio (LR) method proposed in this study was used to transfer calibration to the closest spectral bands for 1 min synchronous data for air masses between 2 and 5, and it was compared to the state-of-the-art Langley calibration technique. The study was conducted at two different locations, Izaña Observatory (IZO) and Valladolid, where measurements were collected almost simultaneously over a 6-month period under different aerosol regimes. In terms of calibration aspects, our results showed very low relative differences and standard deviations in the calibration constant transferred in IZO from the PFR to the Cimel: up to 0.29 % and 0.46 %, respectively, once external factors such as different fields of view between photometers or the presence of calibration issues were considered. However, these differences were higher in the comparison performed at Valladolid (1.04 %) and in the shorter-wavelength spectral bands (up to 0.78 % in IZO and 1.61 % in Valladolid). Additionally, the LR method was successfully used to transfer calibrations between different versions of the CE318-T photometer, providing an accurate calibration transfer (0.17 % to 0.69 %) in the morning LRs, even when the instruments had differences in their central wavelengths (Δλ up to 91 nm). Overall, our results indicate that the LR method is a useful tool not only for transferring calibrations but also for detecting and correcting possible instrumental issues. This is exemplified by the temperature dependence of the signal on the two Cimel UV spectral bands, which was estimated by means of the LR method, resulting in a signal rate of change of approximately -0.09×10-2 per degree in the case of 380 nm and approximately -0.03×10-2 per degree in the case of 340 nm. This estimation allowed us to implement the first operative temperature correction on ultraviolet (UV) spectral bands.

A Multiscale Delayed Channel Attention Network-Based Method for Pansharpening

Nowadays, remote sensing images are widely used in many fields. To obtain high-quality remote sensing images, remote sensing image fusion methods have attracted much attention. Although convolutional neural network-based pansharpening methods have good results, these methods focus on the forward propagation of the network, which cannot effectively seek the mapping relationship between images. Moreover, it is difficult to obtain global information due to the limitations of convolutional operations. In this paper, we propose a pansharpening method based on multiscale delayed channel attention networks. The method iteratively seeks to correlate high-resolution stage features with the original low-resolution multispectral image, providing a mechanism for error feedback to map the error of each stage. Meanwhile, it designs a multiscale feature fusion module to fuse feature information from different fields of view. The design of the delayed channel attention mechanism makes the network acquire the association relationship between low-frequency information and high-frequency information through adaptive learning, giving different weights to high-frequency information, and making it more flexible in dealing with different types of information. Finally, the feature aggregation module is used to generate fused images and adjust the corresponding feature information. The experimental results obtained from the Gaofen-2 and WorldView-2 experimental data show that the method achieves a significant improvement compared to the current fusion algorithms.

A steel surface defect detection model based on graph neural networks

Steel is an indispensable raw material in the construction industry. To avert catastrophic events such as building collapse, it is essential to detect minute defects on steel surfaces during production. However, this has been a persistent challenge due to the minuscule and dense nature of these defects. To this end, we propose an efficient defect detector called Vision Grapher with Hadamard, which employs a novel attention mechanism (HDmA) to establish local-to-local relationships within an image and integrates global relationships by graph convolution. With the HDmA module, we can not only fuse information under the same field of view, but also under different fields of view, which significantly enhances the richness of the acquired features. In addition, compared to convolutional neural networks, graph neural networks can utilize the contextual information in the image more effectively and resulting in better performance. We evaluate our model on the NEU-DET and GC-10 benchmark datasets, which encompass six and ten types of defects on the surfaces of hot-rolled and cold-rolled steel, and our model achieves a mean average precision of 79.04% and 66.93% on the two datasets, respectively. The results demonstrate that our model significantly improves the accuracy of defect detection compared to existing methods.