High-resolution Camera Images Research Articles

OGBN P23 Diagnosing and mapping Barrett's oesophagus: a need to be better

Abstract Background The diagnosis of Barrett's oesophagus is made by endoscopic assessment of the oesophageal epithelium and histopathological confirmation of intestinal metaplasia on oesophageal biopsies. There are clear standards for the diagnosis of Barrett's oesophagus described by the British Society of Gastroenterologists (BSG). It is vital to maintain these standards to ensure accuracy of diagnosis (to prevent both over-diagnosis and under-diagnosis) and to ensure that conversion to dysplasia or neoplasia is not missed. This study aimed to assess the quality of Barrett's surveillance at our institution and implement changes in our service to improve diagnosis. Methods All patients who were due to have Barrett's surveillance endoscopy in 2022 were identified from our electronic hospital waiting lists. Initial endoscopy reports, where the Barrett's was diagnosed, were obtained and assessed for quality of adherence to BSG standards, such as image capture, number of biopsies, recording of Prague classification, use of high-definition screens and use of adjuncts (such as infacol or acetic acid). Histopathological reports were obtained and assessed for correlation with endoscopic findings. Results 192 patients were identified for this study. All had Barrett's oesophagus diagnosed between 2016 and 2020, either on endoscopic grounds, histopathological suggestion of intestinal metaplasia, or both. A total of 29 different endoscopists (including consultant gastroenterologists, surgeons, trainees, nurse endoscopists and endoscopists from outsourcing companies) had performed the primary diagnostic scope in this cohort. 55 patients (29%) did not have any images captured and recorded on their endoscopy report. 36 patients (19%) did not have a Prague classification recorded. Only 127 patients (66%) had intestinal metaplasia on biopsies. p53 status was not recorded in any case. Conclusions This study highlights several deficiencies in the current practice of diagnosis of Barrett's oesophagus and these findings may be replicated in other units. These data have been used to develop a wide-ranging quality improvement programme for Barrett's surveillance, including dedicated Barrett's lists shared amongst a small number of experienced endoscopists, use of a high resolution scope and camera system, image capture and appropriate 'pointing' of procedures to allow enough time for accurate mapping and use of endoscopic adjuncts.

In-situ 3D contour measurement for laser powder bed fusion based on phase guidance

In-situ layerwise imaging measurement of laser powder bed fusion (LPBF) provides a wealth of forming and defect data which enables monitoring of components quality and powder bed homogeneity. Using high-resolution camera layerwise imaging and image processing algorithms to monitor fusion area and powder bed geometric defects has been studied by many researchers, which successfully monitored the contours of components and evaluated their accuracy. However, research for the methods of in-situ 3D contour measurement or component edge warping identification is rare. In this study, a 3D contour measurement method combining gray intensity and phase difference is proposed, and its accuracy is verified by designed experiments. The results show that the high-precision of the 3D contours can be achieved by the constructed energy minimization function. This method can detect the deviations of common geometric features as well as warpage at LPBF component edges, and provides fundamental data for in-situ quality monitoring tools.

The Analysis of Cones within the Tianwen-1 Landing Area

On 15 May 2021, the Zhurong rover of China’s first Mars mission, Tianwen-1 (TW-1), successfully landed in southern Utopia Planitia on Mars. Various landforms were present in the landing area, and this area recorded a complex geological history. Cones are one of the typical landforms in the landing area and Utopia Planitia, and they have a great significance to the local geological processes due to the diversity of their origins. Using High-Resolution Imaging Camera (HiRIC) images collected by the TW-1 orbiter, we identified a total of 272 well-preserved circular cones in the landing area. Detailed surveys of their spatial distribution, morphological characteristics, and morphometric parameters were conducted. A preliminary analysis of the surface characteristics of these cones also provides additional information to strengthen our understanding of them. The results of the high-resolution topographic analysis show that the cone heights are in the range of 10.5–90.8 m and their basal diameters range from 178.9–1206.6 m. We compared the morphometric parameters of the cones in the landing area with terrestrial and Martian analogous features and found that our measured cones are consistent with the ranges of mud volcanoes and also a small subset of igneous origin cones. However, the result of spatial analysis is more favorable to mud volcanoes, and the lower thermal inertia of the cones in the landing area compared to their surrounding materials is also a typical characteristic of mud volcanoes. Based on current evidence and analysis, we favor interpreting the cones in the TW-1 landing area as mud volcanoes.

Three-Dimensional Measurement and Three-Dimensional Printing of Giant Coastal Rocks

In recent years, the use of three-dimensional (3D) measurement and printing technologies has become an effective means of analyzing and reproducing both physical and natural objects, regardless of size. However, in some complex environments, such as coastal environments, it is difficult to obtain the required data by conventional measurement methods. In this paper, we describe our efforts to archive and digitally reproduce a giant coastal rock formation known as Sanouiwa, a famous site off the coast of Miyako City, Iwate Prefecture, Japan. We used two different 3D measurement techniques. The first involved taking pictures using a drone-mounted camera, and the second involved the use of global navigation satellite system data. The point cloud data generated from the high-resolution camera images were integrated using 3D shape reconstruction software, and 3D digital models were created for use in tourism promotion and environmental protection awareness initiatives. Finally, we fabricated the 3D digital models of the rocks with 3D printers for use as museum exhibitions, school curriculum materials, and related applications.

ExoNet Database: Wearable Camera Images of Human Locomotion Environments.

ExoNet Database: Wearable Camera Images of Human Locomotion Environments.

High-throughput measurement of coefficient of thermal expansion using a high-resolution digital single-lens reflex camera and digital image correlation.

High-throughput measurement of thermal deformation and determination of coefficient of thermal expansion (CTE) using a high-resolution digital single lens reflex (DSLR) camera and digital image correlation (DIC) is described. To mitigate the mosaic effect caused by the Bayer filter of DSLR cameras, a color image pre-processing method, which adjusts the brightness and equalizes the color channels of the raw image, is carried out. In addition, a Gaussian pre-filtering step is adopted for denoising the images captured with DSLR cameras to enhance the subpixel registration accuracy. Then, by processing the recorded images using the state-of-the-art DIC algorithm, full-field displacements and strains can be determined. Compared with conventional industrial cameras, a DSLR camera offers not only portability, compactness, and economy but also much higher resolution of recorded images, allowing CTE characterization with higher throughput. Real experiments, including a verification experiment of the color image pre-processing technique, a benchmark CTE determination of Al alloy, and a high-throughput CTE determination of 15 samples of three different metals, validated the feasibility and accuracy of the proposed technique. The proposed method is cost-effective and time-saving, showing great potential in the high-throughput CTE measurement and other high-throughput strain measurement scenarios.

Giordano Bruno: Small crater populations––Implications for self-secondary cratering

Giordano Bruno is a lunar farside Copernican-age crater. The relatively few superposed impact craters on its floor and ejecta blanket and extensive bright rays indicate its youth. High-resolution Lunar Reconnaissance Orbiter Camera images reveal that the frequency and the characteristics of the cumulative size-frequency distributions of the small-diameter impact craters and their morphology vary across the clastic ejecta and impact melt covered surfaces. Crater frequencies (N(10) defined as ≥10 m km−2) vary by a factor of 10 s–100 s (N(10) 2–700) across the ejecta blanket, and between the ejecta and the melt deposits. Numerous craters on the ejecta blanket are degraded and buried by debris and impact melt, indicating that these partially buried craters formed during the deposition of the ejecta and prior to or during the emplacement of the impact melt. From geologic relations and crater statistics we conclude that a significant fraction of the craters observed on the ejecta blanket and the melt were formed during the cratering process itself and represent "self-secondaries." Further, we conclude that these craters do not represent an extra-lunar primary impact production population. Self-secondary craters are formed by material launched into near-vertical trajectories and having velocities such that their flight time is sufficiently long that the bulk of the clastic ejecta and impact melt are deposited before that material impacts the surface. The presence of a significant number of self-secondary craters on the ejecta makes the determination of relative and absolute age dates problematic. Crater counts would indicate an inappropriately old age. Using data for craters on the melt surfaces and for small-diameter bright ejecta craters, an absolute model age of 1 Ma is estimated. This age is considerably younger than that estimated by other studies and probably represents a maximum age.

Online quality inspection using Bayesian classification in powder-bed additive manufacturing from high-resolution visual camera images

Despite their advances and numerous benefits, metal powder-bed additive manufacturing (AM) processes still suffer from the high chances of defect formation and a need for improved quality. This work develops an online monitoring system for quality of fusion and defect formation in every layer of the laser powder-bed fusion process using computer vision and Bayesian inference. An imaging setup is developed that for the first time allows capturing in-situ (during the build) images from every layer that visualize detailed layer defects and porosity. A database of camera images from every layer of AM parts made with various part quality was created that is the first visual labeled dataset from in-situ visual images of the powder-bed AM (also visualizing detailed layer features). The dataset is used in training-based classification to detect layers or sub-regions of the layer with low quality of fusion or defects. Features are carefully selected based on physical intuition into the process and extracted from the images of the various types of builds. A Bayesian classifier is developed and trained to classify the quality of the build that signifies the defective and unacceptable build layers or regions. The results can be used for quasi-real-time (layer-wise) process control, further process decisions, or corrective actions.

CORRECTION AND DENSIFICATION OF UAS-BASED PHOTOGRAMMETRIC THERMAL POINT CLOUD

Photogrammetric processing algorithms can suffer problems due to either the initial image quality (noise, low radiometric quality, shadows and so on) or to certain surface materials (shiny or textureless objects). This can result in noisy point clouds and/or difficulties in feature extraction. Specifically, dense point clouds which are generated with photogrammetric method using a lightweight thermal camera, are more noisy and sparse than the point clouds of high-resolution digital camera images. In this paper, new method which produces more reliable and dense thermal point cloud using the sparse thermal point cloud and high resolution digital point cloud was considered. Both thermal and digital images were obtained with UAS (Unmanned Aerial System) based lightweight Optris PI 450 and Canon EOS 605D camera images. Thermal and digital point clouds, and orthophotos were produced using photogrammetric methods. Problematic thermal point cloud was transformed to a high density thermal point cloud using image processing methods such as rasterizing, registering, interpolation and filling. The results showed that the obtained thermal point cloud - up to chosen processing parameters - was 87% more densify than the original point cloud. The second improvement was gained at the height accuracy of the thermal point cloud. New densified point cloud has more consistent elevation model while the original thermal point cloud shows serious deviations from the expected surface model.

CORRECTION AND DENSIFICATION OF UAS-BASED PHOTOGRAMMETRIC THERMAL POINT CLOUD

Abstract. Photogrammetric processing algorithms can suffer problems due to either the initial image quality (noise, low radiometric quality, shadows and so on) or to certain surface materials (shiny or textureless objects). This can result in noisy point clouds and/or difficulties in feature extraction. Specifically, dense point clouds which are generated with photogrammetric method using a lightweight thermal camera, are more noisy and sparse than the point clouds of high-resolution digital camera images. In this paper, new method which produces more reliable and dense thermal point cloud using the sparse thermal point cloud and high resolution digital point cloud was considered. Both thermal and digital images were obtained with UAS (Unmanned Aerial System) based lightweight Optris PI 450 and Canon EOS 605D camera images. Thermal and digital point clouds, and orthophotos were produced using photogrammetric methods. Problematic thermal point cloud was transformed to a high density thermal point cloud using image processing methods such as rasterizing, registering, interpolation and filling. The results showed that the obtained thermal point cloud - up to chosen processing parameters - was 87% more densify than the original point cloud. The second improvement was gained at the height accuracy of the thermal point cloud. New densified point cloud has more consistent elevation model while the original thermal point cloud shows serious deviations from the expected surface model.

Tensile failure of laminates containing an embedded wrinkle; numerical and experimental study

The failure of a quasi-isotropic composite laminate containing an embedded out-of-plane fibre wrinkle defect was investigated under tension loading. Laboratory test specimens with controlled severity of fibre waviness were manufactured. Along with recording load–displacement data, high resolution camera images were taken at regular intervals which monitored the initiation and interaction of different damage mechanisms during test. Three-dimensional FE models were built following the geometry of actual test specimens. The information obtained from the tests was used to develop user material subroutines, implemented in Abaqus/Explicit as continuum damage and cohesive zone models for intra- and inter-ply failure respectively. The results of the simulations showed very good correlation with test observations in terms of failure load, location of damage initiation and interaction between different damage mechanisms for a range of waviness cases tested.

Robust curb detection with fusion of 3D-Lidar and camera data.

Curb detection is an essential component of Autonomous Land Vehicles (ALV), especially important for safe driving in urban environments. In this paper, we propose a fusion-based curb detection method through exploiting 3D-Lidar and camera data. More specifically, we first fuse the sparse 3D-Lidar points and high-resolution camera images together to recover a dense depth image of the captured scene. Based on the recovered dense depth image, we propose a filter-based method to estimate the normal direction within the image. Then, by using the multi-scale normal patterns based on the curb's geometric property, curb point features fitting the patterns are detected in the normal image row by row. After that, we construct a Markov Chain to model the consistency of curb points which utilizes the continuous property of the curb, and thus the optimal curb path which links the curb points together can be efficiently estimated by dynamic programming. Finally, we perform post-processing operations to filter the outliers, parameterize the curbs and give the confidence scores on the detected curbs. Extensive evaluations clearly show that our proposed method can detect curbs with strong robustness at real-time speed for both static and dynamic scenes.

High-resolution 3D surface strain magnitude using 2D camera and low-resolution depth sensor

Generating 2-D strain maps of the face during facial expressions provides a useful feature that captures the bio-mechanics of facial skin tissue, and has had wide application in several research areas. However, most applications have been restricted to collecting data on a single pose. Moreover, methods that strictly use 2-D images for motion estimation can potentially suppress large strains because of projective distortions caused by the curvature of the face. This paper proposes a method that allows estimation of 3-D surface strain using a low-resolution depth sensor. The algorithm consists of automatically aligning a rough approximation of a 3-D surface with an external high resolution camera image. We provide experimental results that demonstrate the robustness of the method on a dataset collected using the Microsoft Kinect synchronized with two external high resolution cameras, as well as 101 subjects from a publicly available 3-D facial expression video database (BU4DFE).

Exterior orientation of CBERS-2B imagery using multi-feature control and orbital data

The major contribution of this paper relates to the practical advantages of combining Ground Control Points (GCPs), Ground Control Lines (GCLs) and orbital data to estimate the exterior orientation parameters of images collected by CBERS-2B (China–Brazil Earth Resources Satellite) HRC (High-resolution Camera) and CCD (High-resolution CCD Camera) sensors. Although the CBERS-2B is no longer operational, its images are still being used in Brazil, and the next generations of the CBERS satellite will have sensors with similar technical features, which motivates the study presented in this paper. The mathematical models that relate the object and image spaces are based on collinearity (for points) and coplanarity (for lines) conditions. These models were created in an in-house developed software package called TMS (Triangulation with Multiple Sensors) with multi-feature control (GCPs and GCLs). Experiments on a block of four CBERS-2B HRC images and on one CBERS-2B CCD image were performed using both models. It was observed that the combination of GCPs and GCLs provided better bundle block adjustment results than conventional bundle adjustment using only GCPs. The results also demonstrate the advantages of using primarily orbital data when the number of control entities is reduced.

Parallel implementation of background subtraction algorithms for real-time video processing on a supercomputer platform

Results of evaluation of the background subtraction algorithms implemented on a supercomputer platform in a parallel manner are presented in the article. The aim of the work is to chose an algorithm, a number of threads and a task scheduling method, that together provide satisfactory accuracy and efficiency of a real-time processing of high-resolution camera images, maintaining the cost of resources usage at a reasonable level. Two selected algorithms: the Gaussian mixture models and the Codebook, are presented and their computational complexity is discussed. Various approaches to the parallel implementation, including assigning the image pixels to threads, the task scheduling methods and the thread management systems, are presented. The experiments were performed on a supercomputer cluster, using a single machine with 12 physical cores. The accuracy and performance of the implemented algorithms were evaluated for varying image resolutions and numbers of concurrent processing threads. On a basis of the evaluation results, an optimal configuration for the parallel implementation of the system for real-time video content analysis on a supercomputer platform was proposed.

AN APPLICATION OF MATTING LAPLACIAN MATRIX TO RANGE IMAGE SUPER-RESOLUTION

This paper describes a successful application of Matting Laplacian Matrix to the problem of generating high-resolution range images. The Matting Laplacian Matrix in this paper exploits the fact that discontinuities in range and coloring tend to co-align, which enables us to generate high-resolution range image by integrating regular camera image into the range data. Using one registered and potentially high-resolution camera image as reference, we iteratively refine the input low-resolution range image, in terms of both spatial resolution and depth precision. We show that by using such a Matting Laplacian Matrix, we can get high-quality high-resolution range images.

Low-cost geo-data acquisition for the urban built environment

In the urban environment there is a need for new and renovated building façades to be created in harmony with the existing environment. This paper describes a simple approach to the acquisition of geo-data. An off-the-shelf software package together with low-cost equipment was used to collect building inventory data from a combination of high-resolution digital and video camera images, digital close-range photogrammetry techniques and geographic information systems. The method consists of three stages. First the potential of geo-data acquisition is investigated by using a video camera and a digital camera. The second stage outlines the metric survey for the management of building façade inventory data for geographical information systems in making correct decisions in urban areas. The third stage explains how video camera images can be used to obtain attribute data related to different uses. The methodology developed was tested in a street in Ankara, the capital city of Turkey. It is concluded that this low-cost method using off-the-shelf software offers many advantages and benefits in different expertise fields, particularly for local governments and municipalities.

Hesperian equatorial thermokarst lakes in Ares Vallis as evidence for transient warm conditions on Mars

On Earth, permafrost thawing is linked to climate warming. Similarly, on Mars, permafrost degradation, described from mid-latitude and equatorial settings, is likely linked to global or regional climate change. Putative thermokarst depressions identified on Mars are widely considered to be the result of sublimation, evaporation, or thawing of an ice-rich substrate. The possibility that the depressions formed by melting of permafrost to create alas-like lakes has been recently proposed, but is controversial, owing to the lack of primary evidence for liquid filling the depressions. Here we use high-resolution Mars Reconnaissance Orbiter Context Camera images and derived topographic data to characterize possible thermokarst terrain in Ares Vallis. The terrain comprises subcircular to irregular, flat-floored rimless topographic depressions that occur at varying elevations. We report the discovery of narrow channels connecting thermokarst-like depressions that provide evidence for the previous presence of ponded liquid water. Crater counts on these surfaces indicate resurfacing that is likely related to flood deposition of water-saturated sediments in Ares Vallis during the Hesperian (ca. 3.6–3.0 Ga). We infer that thermokarst lakes formed after flooding by thawing of ice within the sediments during transient warm periods in the Hesperian, a time previously considered to be too cold to permit ice thaw.

Remote sensing monitoring of tobacco field based on phenological characteristics and time series image—A case study of Chengjiang County, Yunnan Province, China

Using three-phase remote sensing images of China-Brazil Earth Resources Satellite 02B (CBERS02B) and Landsat-5 TM, tobacco field was extracted by the analysis of time series image based on the different phenological characteristics between tobacco and other crops. The spectral characteristics of tobacco and corn in luxuriant growth stage are very similar, which makes them difficult to be distinguished using a single-phase remote sensing image. Field film after tobacco seedlings transplanting can be used as significant sign to identify tobacco. Remote sensing interpretation map based on the fusion image of TM and CBERS02B’s High-Resolution (HR) camera image was used as standard reference material to evaluate the classification accuracy of Spectral Angle Mapper (SAM) and Maximum Likelihood Classifier (MLC) for time series image based on full samples test method. SAM has higher classification accuracy and stability than MLC in dealing with time series image. The accuracy and Kappa of tobacco coverage extracted by SAM are 83.4% and 0.692 respectively, which can achieve the accuracy required by tobacco coverage measurement in a large area.

Fluvial morphology of Naktong Vallis, Mars: A late activity with multiple processes

The morphology of fluvial valleys on Mars provides insight into surface and subsurface hydrology, as well as to Mars’ past climate. In this study, Naktong Vallis and its tributaries were examined from high-resolution stereoscopic camera (HRSC) images, thermal emission imaging system (THEMIS) daytime IR images, and mars orbiter laser altimeter (MOLA) data. Naktong Vallis is the southern part of a very large fluvial basin composed by Mamers, Scamander, and Naktong Vallis with a total length of 4700 km, and is one of the largest fluvial system on Mars. Naktong Vallis incised along its path a series of smooth intercrater plains. Naktong's main valley cut smooth plains during the Early Hesperian period, estimated ∼3.6–3.7 Gyr, implying a young age for the valley when compared to usual Noachian-aged valley networks. Branching valleys located in degraded terrains south of the main Naktong valley have sources inside a large plateau located at more than 2000 m elevation. Connections between these valleys and Naktong Vallis have been erased by the superimposition of late intercrater plains of Early to Late Hesperian age, but it is likely that this plateau represents the main source of water. Small re-incisions of these late plains show that there was at least one local reactivation. In addition, valley heads are often amphitheatre-shaped. Despite the possibility of subsurface flows, the occurrence of many branching valleys upstream of Naktong's main valley indicate that runoff may have played an important role in Naktong Vallis network formation. The importance of erosional landforms in the Naktong Vallis network indicates that fluvial activity was important and not necessarily lower in the Early Hesperian epoch than during the Noachian period. The relationships between overland flows and sapping features suggest a strong link between the two processes, rather than a progressive shift from surface to subsurface flow.