Image Acquisition Geometry Research Articles

Evaluating night-time light sources and correlation with socio-economic development using high-resolution multi-spectral Jilin-1 satellite imagery of Quito, Ecuador

ABSTRACT Artificial light at night (ALAN) has positive and negative effects on social, economic, environmental, and ecological systems, and will increase with urban expansion. In this study, we used a multi-spectral 1.5 m resolution night-time acquisition from a Jilin-1 satellite over the city of Quito, Ecuador, to evaluate spatial lighting patterns in an expanding and topography complex-built environment. We demonstrated a requirement for robust georeferencing and orthorectification due to the complex topography, with errors on the order of 4–6 pixels (5.8–8.4 m CE95). We also quantified differences in observed brightness due to the image acquisition and local geometry. Street light type was distinguishable between high-pressure sodium (HPS) and light emitting diode (LED) sources (F1-score = 0.72–0.83) using a shark random forest decision tree approach. Additionally, street lights could be located within 10 m (F1-score = 0.71) with balanced omissions and commissions. Spatial trends revealed that the road network was the dominant source of illumination, accounting for 45% of illuminated pixels, whereas built-up areas accounted for 23%. Overall, 68% of all illuminated pixels were on or within 10 m of the road. Higher socio-economic development was associated with higher proportions of LED lighting, greater road network lighting and density of street lights, higher overall radiance for built-up areas and the road network, and greater coverage and illumination of designated green spaces. The broad impacts of ALAN mean that addressing the causes and consequences of lighting inequalities is a complex issue. Nonetheless, Jilin-1 night-time imagery offers a low-cost way to map and monitor light sources at high-resolution that will be beneficial to city-planners and progressing Sustainable Development Goals.

Solar illumination effects on the dry-season variability of spectral and spatial attributes calculated from PlanetScope data over tropical forests of the Amazon

ABSTRACT The spectral variability of tropical forests during the Amazonian dry season is not entirely understood because of the divergent responses in Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation indices (VIs) measured under-increased water deficit and high insolation. Here, we used a dataset composed of 493 cloud-free PlanetScope (PS) images to investigate possible effects of solar illumination on the dry-season variability of spectral and spatial attributes. The attributes were calculated from June to September over dense tropical forests of the Amazon. The dry-season images were obtained at nadir viewing between 2017 and 2019 over 12 selected sites representing different climatic and environmental conditions. To detect dry-season patterns of vegetation brightness with changes in the geometry of image acquisition, we applied principal component analysis (PCA) over the PS surface reflectance. We plotted the average surface reflectance (2017–2019) for each of the four PS bands and inspected the variability of two VIs with distinct levels of anisotropy to bidirectional effects: the Enhanced Vegetation Index (EVI) and the Normalized Difference Vegetation Index (NDVI). We also investigated the signal of textural metrics from Grey Level Co-occurrence Matrix (GLCM) obtained from the near-infrared (NIR) band of PS. Finally, we generated shade fractions from Spectral Mixture Analysis (SMA), correlated the spectral and spatial attributes of vegetation with solar angles, and observed the dry-season variability in reflectance and VIs over pseudo-invariant soil surfaces. The results showed the existence of solar illumination effects on PS image acquisition during the dry season of the Amazon, which affected differently the NDVI and EVI. From the beginning (June) to the end (September) of the dry season, the solar zenith angle (SZA) decreased and the solar azimuth angle (SAA) increased during the period of acquisition of the PS images. The amplitude of SZA between June and September increased towards south of the Amazon, while the amplitude of SAA increased towards north of this region. Changes in vegetation brightness from June to September were captured by PCA over some sites. Because of the overall increase in both red and NIR band reflectance, solar illumination effects were compensated during the NDVI calculation. In contrast, because the EVI is largely driven by changes in NIR reflectance, these effects contributed to increase the EVI signal at the end of the dry season. For most sites, GLCM texture mean increased towards the end of the dry season, while texture variance decreased in the opposite direction. Shade fractions decreased towards September when reduced amounts of canopy shadows were sensed by PS. EVI was more anisotropic than NDVI and presented higher negative correlations with SZA and shade fractions and higher positive correlations with SAA and texture mean. The dry-season increase in EVI with solar illumination effects was also observed over pseudo-invariant soil surfaces. From this unprecedent scale of observations at high spatial and temporal resolutions, we recommend caution when using anisotropic VIs for large-scale phenological studies over the Amazon because biophysical and non-biophysical signals may be coupled together.

Multimodal Registration of Optical Images and Digital Elevation Models Using Terrain Features

Registration of multimodal images such as optical data and digital elevation models (DEM) is a challenging task due to significant non-linear differences between these images. To address the problem, this paper proposes a new robust approach to integrate optical images and DEMs by using terrain features. In order to detect these features, a simulated image is generated based on the DEM by illuminating it in the geometry of the optical image acquisition, such that typical textures induced by topography are well present as those in the optical image. Hence, the multimodal registration is performed on the optical data and the simulated image to maximize the accuracy of feature matching. The Affine Scale-Invariant Feature Transform (ASIFT) is used to detect keypoints from the two images. Correspondences are matched through the nearest neighbor distance ratio, and outliers are removed using a two-step elimination procedure. The proposed method has been tested on five pairs of optical-DEM images with various spatial resolutions. Experimental results have shown that this method can provide robust registration for optical-DEM images with high accuracies of sub pixel level. The novelty of proposed method is to make use of terrain features for registration, providing a new perspective for the integration of multimodal images.

How Image Acquisition Geometry of UAV Campaigns Affects the Derived Products and Their Accuracy in Areas with Complex Geomorphology

The detailed and accurate mapping of landscapes and their geomorphological characteristics is a key issue in hazard management. The current study examines whether the image acquisition geometry of unmanned aerial vehicle (UAV) campaigns affects the accuracy of the derived products, i.e., orthophotos, digital surface models (DSMs) and photogrammetric point clouds, while performing a detailed geomorphological mapping of a landslide area. UAV flights were executed and the collected imagery was organized into three subcategories based on the viewing angle of the UAV camera. The first subcategory consists of the nadir imagery, the second is composed of the oblique imagery and the third category blends both nadir and oblique imagery. UAV imagery processing was carried out using structure-from-motion photogrammetry (SfM). High-resolution products were generated, consisting of orthophotos, DSMs and photogrammetric-based point clouds. Their accuracy was evaluated utilizing statistical approaches such as the estimation of the root mean square error (RMSE), calculation of the geometric mean of a feature, length measurement, calculation of cloud-to-cloud distances as well as qualitive criteria. All the quantitative and qualitative results were taken into account for the impact assessment. It was demonstrated that the oblique-viewing geometry as well as the combination of nadir and oblique imagery could be used effectively for geomorphological mapping in areas with complex topography and steep slopes that overpass 60 degrees. Moreover, the accuracy assessment revealed that those acquisition geometries contribute to the creation of significantly better products compared to the corresponding one arising from nadir-viewing imagery.

3D Reconstruction of Coastal Cliffs from Fixed-Wing and Multi-Rotor UAS: Impact of SfM-MVS Processing Parameters, Image Redundancy and Acquisition Geometry

Monitoring the dynamics of coastal cliffs is fundamental for the safety of communities, buildings, utilities, and infrastructures located near the coastline. Structure-from-Motion and Multi View Stereo (SfM-MVS) photogrammetry based on Unmanned Aerial Systems (UAS) is a flexible and cost-effective surveying technique for generating a dense 3D point cloud of the whole cliff face (from bottom to top), with high spatial and temporal resolution. In this paper, in order to generate a reproducible, reliable, precise, accurate, and dense point cloud of the cliff face, a comprehensive analysis of the SfM-MVS processing parameters, image redundancy and acquisition geometry was performed. Using two different UAS, a fixed-wing and a multi-rotor, two flight missions were executed with the aim of reconstructing the geometry of an almost vertical cliff located at the central Portuguese coast. The results indicated that optimizing the processing parameters of Agisoft Metashape can improve the 3D accuracy of the point cloud up to 2 cm. Regarding the image acquisition geometry, the high off-nadir (90°) dataset taken by the multi-rotor generated a denser and more accurate point cloud, with lesser data gaps, than that generated by the low off-nadir dataset (3°) taken by the fixed wing. Yet, it was found that reducing properly the high overlap of the image dataset acquired by the multi-rotor drone permits to get an optimal image dataset, allowing to speed up the processing time without compromising the accuracy and density of the generated point cloud. The analysis and results presented in this paper improve the knowledge required for the 3D reconstruction of coastal cliffs by UAS, providing new insights into the technical aspects needed for optimizing the monitoring surveys.

Calibration of Satellite Low Radiance by AERONET-OC Products and 6SV Model

For water quality monitoring using satellite data, it is often required to optimize the low radiance signal through the application of radiometric gains. This work describes a procedure for the retrieval of radiometric gains to be applied to OLI/L8 and MSI/S2A data over coastal waters. The gains are defined by the ratio of the top of atmosphere (TOA) reflectance simulated using the Second Simulation of a Satellite Signal in the Solar Spectrum—vector (6SV) radiative transfer model, REF, and the TOA reflectance acquired by the sensor, MEAS, over AERONET-OC stations. The REF is simulated considering quasi-synchronous atmospheric and aquatic AERONET-OC products and the image acquisition geometry. Both for OLI/L8 and MSI/S2A the measured TOA reflectance was higher than the modeled signal in almost all bands resulting in radiometric gains less than 1. The use of retrieved gains showed an improvement of reflectance remote sensing, Rrs, when with ACOLITE atmospheric correction software. When the gains are applied an accuracy improvement of the Rrs in the 400–700 nm domain was observed except for the first blue band of both sensors. Furthermore, the developed procedure is quick, user-friendly, and easily transferable to other optical sensors.

Geometrically variable three-dimensional ultrasound for mechanically assisted image-guided therapy of focal liver cancer tumors.

Image-guided focal ablation procedures are first-line therapy options in the treatment of liver cancer tumors that provide advantageous reductions in patient recovery times and complication rates relative to open surgery. However, extensive physician training is required and image guidance variabilities during freehand therapy applicator placement limit the sufficiency of ablation volumes and the overall potential of these procedures. We propose the use of three-dimensional ultrasound (3D US) to provide guidance and localization of therapy applicators, augmenting current ablation therapies without the need for specialized procedure suites. We have developed a novel scanning mechanism for geometrically variable 3D US images, a mechanical tracking system, and a needle applicator insertion workflow using a custom needle applicator guide for targeted image-guided procedures. A three-motor scanner was designed to use any commercially available US probe to generate accurate, consistent, and geometrically variable 3D US images. The designed scanner was mounted on a counterbalanced stabilizing and mechanical tracking system for determining the US probe orientation, which was assessed using optical tracking. Further exploiting the utility of the motorized scanner, an image-guidance workflow was developed that moved the probe to any identified target within an acquired 3D US image. The complete 3D US guidance system was used to perform mock targeted interventional procedures on a phantom by selecting a target in a 3D US image, navigating to the target, and performing needle insertion using a custom 3D-printed needle applicator guide. Registered postinsertion 3D US images and cone-beam computed tomography (CBCT) images were used to evaluate tip targeting errors when using the motors, tracking system, or mixed navigation approaches. Two 3D US image geometries were investigated to assess the accuracy of a small-footprint tilt approach and a large field-of-view hybrid approach for a total of 48 targeted needle insertions. 3D US image quality was evaluated in a healthy volunteer and compared to a commercially available matrix array US probe. A mean positioning error of 1.85±1.33mm was observed when performing compound joint manipulations with the mechanical tracking system. A combined approach for navigation that incorporated the motorized movement and the in-plane tracking system corrections performed the best with a mean tip error of 3.77±2.27mm and 4.27±2.47mm based on 3D US and CBCT images, respectively. No significant differences were observed between hybrid and tilt image acquisition geometries with all mean registration errors ≤1.2mm. 3D US volunteer images resulted in clear reconstruction of clinically relevant anatomy. A mechanically tracked system with geometrically variable 3D US provides a utility that enables enhanced applicator guidance, placement verification, and improved clinical workflow during focal liver tumor ablation procedures. Evaluations of the tracking accuracy, targeting capabilities, and clinical imaging feasibility of the proposed 3D US system, provided evidence for clinical translation. This system could provide a workflow for improving applicator placement and reducing local cancer recurrence during interventional procedures treating liver cancer and has the potential to be expanded to other abdominal interventions and procedures.

Detection of Parking Cars in Stereo Satellite Images

In this paper, we present a Remote Sens. approach to localize parking cars in a city in order to enable the development of parking space availability models. We propose to use high-resolution stereo satellite images for this problem, as they provide enough details to make individual cars recognizable and the time interval between the stereo shots allows to reason about the moving or static condition of a car. Consequently, we describe a complete processing pipeline where raw satellite images are georeferenced, ortho-rectified, equipped with a digital surface model and an inclusion layer generated from Open Street Model vector data, and finally analyzed for parking cars by means of an adapted Faster R-CNN oriented bounding box detector. As a test site for the proposed approach, a new publicly available dataset of the city of Barcelona labeled with parking cars is presented. On this dataset, a Faster R-CNN model directly trained on the two ortho-rectified stereo images achieves an average precision of 0.65 for parking car detection. Finally, an extensive empirical and analytical evaluation shows the validity of our idea, as parking space occupancy can be broadly derived in fully visible areas, whereas moving cars are efficiently ruled out. Our evaluation also includes an in-depth analysis of the stereo occlusion problem in view of our application scenario as well as the suitability of using a reconstructed Digital Surface Model (DSM) as additional data modality for car detection. While an additional adoption of the DSM in our pipeline does not provide a beneficial cue for the detection task, the stereo images provide essentially two views of the dynamic scene at different timestamps. Therefore, for future studies, we recommend a satellite image acquisition geometry with smaller incidence angles, to decrease occlusions by buildings and thus improve the results with respect to completeness.

Gudalur Spectral Target Detection (GST-D): A New Benchmark Dataset and Engineered Material Target Detection in Multi-Platform Remote Sensing Data

Target detection in remote sensing imagery, mapping of sparsely distributed materials, has vital applications in defense security and surveillance, mineral exploration, agriculture, environmental monitoring, etc. The detection probability and the quality of retrievals are functions of various parameters of the sensor, platform, target–background dynamics, targets’ spectral contrast, and atmospheric influence. Generally, target detection in remote sensing imagery has been approached using various statistical detection algorithms with an assumption of linearity in the image formation process. Knowledge on the image acquisition geometry, and spectral features and their stability across different imaging platforms is vital for designing a spectral target detection system. We carried out an integrated target detection experiment for the detection of various artificial target materials. As part of this work, we acquired a benchmark multi-platform hyperspectral and multispectral remote sensing dataset named as ‘Gudalur Spectral Target Detection (GST-D)’ dataset. Positioning artificial targets on different surface backgrounds, we acquired remote sensing data by terrestrial, airborne, and space-borne sensors on 20th March 2018. Various statistical and subspace detection algorithms were applied on the benchmark dataset for the detection of targets, considering the different sources of reference target spectra, background, and the spectral continuity across the platforms. We validated the detection results using the receiver operation curve (ROC) for different cases of detection algorithms and imaging platforms. Results indicate, for some combinations of algorithms and imaging platforms, consistent detection of specific material targets with a detection rate of about 80% at a false alarm rate between 10−2 to 10−3. Target detection in satellite imagery using reference target spectra from airborne hyperspectral imagery match closely with the satellite imagery derived reference spectra. The ground-based in-situ reference spectra offer a quantifiable detection in airborne or satellite imagery. However, ground-based hyperspectral imagery has also provided an equivalent target detection in the airborne and satellite imagery paving the way for rapid acquisition of reference target spectra. The benchmark dataset generated in this work is a valuable resourcefor addressing intriguing questions in target detection using hyperspectral imagery from a realistic landscape perspective.

Observing Polar Regions from Space: Comparison between Highly Elliptical Orbit and Medium Earth Orbit Constellations

AbstractContinuous observation of polar regions from space remains an important unsolved technical challenge of great interest for the international meteorological community. This capacity would allow achieving global continuous coverage once combined with the geostationary (GEO) satellite network. From a practical point of view, continuous coverage of polar regions with a small number of spacecraft can be obtained from a constellation of satellites either in highly elliptical orbits (HEO) or in medium Earth orbits (MEO). The study compares HEO and MEO satellite constellations for their capacity to provide continuous imaging of polar regions as function of the viewing zenith angle (VZA) and evaluates the corresponding latitude limits that ensure sufficient overlap with GEO imagery. Earlier studies assumed the latitude boundary of 60° and the VZA range 70°–85° depending on the space mission focus: meteorological purposes or communications. From the detailed analysis of meteorological retrieval requirements, this study suggests that the overlap of the GEO and polar observing systems (HEO or MEO) should occur down to the latitude band 45°–50° with a maximum VZA ranging between 60° and 64°. This coverage requirement can be met with two sets of three-satellite HEO constellations (one for each polar area) or a six-satellite MEO constellation. The 12-h Molniya and 14-, 15-, and 16-h HEO systems have been analyzed and determined to meet these revised requirements. The study demonstrates that the six-satellite 24-h MEO system can provide a suitable solution, which is also beneficial from the point of view of ionizing radiation and image acquisition geometry. Among the HEO systems, the 16-h HEO has some advantages relative to other HEO systems from the point of view of spatial coverage and space radiation.

OA248] Computer-based platform for phase contrast breast imaging

Purpose This paper presents a complete and validated computer-based system dedicated to X-ray phase contrast breast imaging research. The system comprises three main modules: (a) a module for generation of computational breast models, (b) a module for generation of phase-contrast X-ray images from computational phantoms in 2D and 3D acquisition setup, and (c) a module for image reconstruction. Methods The module for computational breast models is based on the BreastSimulator tool, used to generate breast models of various sizes and to compress them to a desired thickness. The module for the generation of phase-contrast images is used to model the image acquisition geometry and formation of X-ray images. The image reconstruction is done with a software tool, based on an in–house built reconstruction techniques class library, which is a dedicated object-oriented library for X-ray based applications. The capability of this system to correctly calculate phase-contrast tomographic images was tested by comparing simulated versus experimental images obtained from anthropomorphic breast phantoms. Three anthropomorphic computational breast phantoms were designed from white and grey resin by using the available stereolithography 3D printer. Experimental projection images were acquired and simulated images were generated, considering a breast tomosynthesis setup. Experiments were conducted at beamline ID17, ESRF. Simulations replicated the experimental setup. Images in a tomosynthesis mode were generated and tomograms were calculated by using the reconstruction module. Results Results show very good visual agreement between simulated and experimentally obtained tomosynthesis images. In addition, selected tomosynthesis images from the physical and computational breast phantoms were quantitatively evaluated for set of imaging parameters such as skewness, kurtosis, the power-law exponent, β , of the power spectrum and fractal dimension. Analysis and the comparison of these parameters between simulated and experimental images also show a very good coincidence. Conclusions The platform is currently used in the process of development of a dedicated breast phantom for phase contrast imaging techniques. The system will be a valuable tool in studying new X-ray imaging techniques based on phase contrast, such as phase contrast tomosynthesis and CT.

Determination of Volcanic Plume Three-Dimensional Structure Using CHRIS/PROBA-1 Multiangular Imagery: Case Study of Mount Etna

The recent development of Earth observation satellites with multiangular capabilities and enhanced spectral resolution has led to preliminary attempts at determining the height of atmospheric scatterers, in particular, of top-cloud heights and smoke plumes originating from forest fires. Inspired by these previous studies, the present work presents an original methodology for the determination of the three-dimensional distribution of high-contrast atmospheric aerosols using multiangular images. The method starts with the approximately known geometry of image acquisition and a set of tie points and uses a linearized and regularized functional model to obtain the position of atmospheric scatterers identified by means of a semiassisted procedure on two or more images. A subsequent application to a CHRIS/PROBA-1 scene of Mount Etna following its eruption on June 14, 2014, allows determining the volcanic plume three-dimensional structure with a precision in the 100–200 m level.

Directional scatter imaging for the stereoscopic tracking of fiducial markers in a single kV exposure.

To demonstrate, via Monte Carlo simulation, that an image obtained from the patient-generated scattered radiation forced to impinge on the detector from a known direction by means of parallel-focused grids, can be used to complement the information conveyed by the primary image, such that accurate stereoscopic three-dimensional localization of fiducial markers can be achieved in a single kV x-ray exposure. A voxelized Zubal phantom was used to model the process of fiducial marker localization. The markers were represented as made of gold and cylindrical in shape with dimensions of 5mm in length and 1mm in diameter. Three such markers were placed in the Zubal phantom at the prostate level. Two gantry-mounted image acquisition geometries were modeled: a single kV imaging system and a dual kV-MV imaging system. The detector was modeled as a 30cm×40cm Gd2 O2 S screen with a thickness of 0.2cm and a resolution of 768×1024 pixels. The PENELOPE Monte Carlo code was used to calculate the absorbed dose in this detector imparted by the transmitted primary and directional scatter radiation. A grayscale conversion was then applied to obtain an image from which the positions of the markers were determined. Two parallel-focused grid geometries were modeled, one based on the standard lead-carbon fiber grids and a proposed modification using tungsten as the shielding material. Absorbed dose in the patient model was also calculated. It is shown that the combination of primary and directional scatter images provides the means for an accurate stereoscopic fiducial marker 3D localization in a single x-ray exposure, provided the antiscatter grids are made thick enough to allow radiation traveling only in a particular direction to reach the detector. For the proposed tungsten grid and the x-ray spectrum used in this work, grid ratios of 20 and thickness of 0.2cm, provide the necessary shielding while for the standard lead grids, a ratio of at least 166 and a thickness of 2cm are needed to obtain discernible directional scatter images. We have shown that it is in principle possible to determine the 3D position of fiducial markers in a single exposure by making use of the radiation scattered by the patient to form an image that complements the information obtained with the primary beam. The method here proposed requires minimal modification of existing clinical hardware.

USE OF UAS FOR THE CONSERVATION OF HISTORICAL BUILDINGS IN CASE OF EMERGENCIES

Abstract. The task of conservation and management of cultural heritage is quite central in Italy, which lists a high number of beautiful architectures. A quick and precise survey may be requested in case of calamity. In the present paper, the most commonly used survey techniques are discussed, focusing on their applications for the conservation of the artistic heritage in case of emergency. Particular attention is given to Unmanned Aerial Systems (UAS) photogrammetry and its potentiality in obtaining good results in terms of speed, cheapness, precision and accuracy, assuring at the same time the safety of the operators in critical situations (e.g. natural disasters). A case study, realized at the Castle of Casalbagliano (Alessandria, Italy), is discussed. Different image block configurations and acquisition geometries (nadiral and oblique images) have been exploited, with the aim of defining useful guidelines for emergencies UAS survey of partially collapsed structures. An application to a significative case study is introduced.

Three-dimensional cascaded system analysis of a 50 µm pixel pitch wafer-scale CMOS active pixel sensor x-ray detector for digital breast tomosynthesis

High-resolution, low-noise x-ray detectors based on the complementary metal-oxide-semiconductor (CMOS) active pixel sensor (APS) technology have been developed and proposed for digital breast tomosynthesis (DBT). In this study, we evaluated the three-dimensional (3D) imaging performance of a 50 µm pixel pitch CMOS APS x-ray detector named DynAMITe (Dynamic Range Adjustable for Medical Imaging Technology). The two-dimensional (2D) angle-dependent modulation transfer function (MTF), normalized noise power spectrum (NNPS), and detective quantum efficiency (DQE) were experimentally characterized and modeled using the cascaded system analysis at oblique incident angles up to 30°. The cascaded system model was extended to the 3D spatial frequency space in combination with the filtered back-projection (FBP) reconstruction method to calculate the 3D and in-plane MTF, NNPS and DQE parameters. The results demonstrate that the beam obliquity blurs the 2D MTF and DQE in the high spatial frequency range. However, this effect can be eliminated after FBP image reconstruction. In addition, impacts of the image acquisition geometry and detector parameters were evaluated using the 3D cascaded system analysis for DBT. The result shows that a wider projection angle range (e.g. ±30°) improves the low spatial frequency (below 5 mm−1) performance of the CMOS APS detector. In addition, to maintain a high spatial resolution for DBT, a focal spot size of smaller than 0.3 mm should be used. Theoretical analysis suggests that a pixelated scintillator in combination with the 50 µm pixel pitch CMOS APS detector could further improve the 3D image resolution. Finally, the 3D imaging performance of the CMOS APS and an indirect amorphous silicon (a-Si:H) thin-film transistor (TFT) passive pixel sensor (PPS) detector was simulated and compared.

Plug-and-Play Priors for Bright Field Electron Tomography and Sparse Interpolation

Many material and biological samples in scientific imaging are characterized by non-local repeating structures. These are studied using scanning electron microscopy and electron tomography. Sparse sampling of individual pixels in a 2D image acquisition geometry, or sparse sampling of projection images with large tilt increments in a tomography experiment, can enable high speed data acquisition and minimize sample damage caused by the electron beam. In this paper, we present an algorithm for electron tomographic reconstruction and sparse image interpolation that exploits the non-local redundancy in images. We adapt a framework, termed plug-and-play (P&P) priors, to solve these imaging problems in a regularized inversion setting. The power of the P&P approach is that it allows a wide array of modern denoising algorithms to be used as a "prior model" for tomography and image interpolation. We also present sufficient mathematical conditions that ensure convergence of the P&P approach, and we use these insights to design a new non-local means denoising algorithm. Finally, we demonstrate that the algorithm produces higher quality reconstructions on both simulated and real electron microscope data, along with improved convergence properties compared to other methods.

A novel approach for a 2D/3D image registration routine for medical tool navigation in minimally invasive vascular interventions

Minimally invasive interventions are frequently aided by 2D projective image guidance. To facilitate the navigation of medical tools within the patient, information from preoperative 3D images can supplement interventional data. This work describes a novel approach to perform a 3D CT data registration to a single interventional native fluoroscopic frame. The goal of this procedure is to recover and visualize a current 2D interventional tool position in its corresponding 3D dataset.A dedicated routine was developed and tested on a phantom. The 3D position of a guidewire inserted into the phantom could successfully be reconstructed for varying 2D image acquisition geometries. The scope of the routine includes projecting the CT data into the plane of the fluoroscopy. A subsequent registration of the real and virtual projections is performed with an accuracy within the range of 1.16±0.17mm for fixed landmarks. The interventional tool is extracted from the fluoroscopy and matched to the corresponding part of the projected and transformed arterial vasculature. A root mean square error of up to 0.56mm for matched point pairs is reached. The desired 3D view is provided by backprojecting the matched guidewire through the CT array.Due to its potential to reduce patient dose and treatment times, the proposed routine has the capability of reducing patient stress at lower overall treatment costs.

SU‐E‐I‐12: Flexible Geometry Computed Tomography

Purpose:The concept separates the mechanical connection between the radiation source and detector. This design allows the trajectory and orientation of the radiation source/detector to be customized to the object that is being imaged. This is in contrast to the formulaic rotation‐translation image acquisition of conventional computed tomography(CT).Background/significance:CT devices that image a full range of: anatomy, patient populations, and imaging procedures are large. The root cause of the expanding size of comprehensive CT is due to the commitment to helical geometry that is hardwired into the image reconstruction. FGCT extends the application of alternative reconstruction techniques, i.e. tomosynthesis, by separating the two main components— radiation source and detector— and allow for 6 degrees of freedom motion for radiation source, detector, or both. The image acquisition geometry is then tailored to how the patient/object is positioned. This provides greater flexibility on the position and location that the patient/object is being imaged. Additionally, removing the need of a rotating gantry reduces the footprint so that CT is more mobile and more available to move to where the patient/object is at, instead of the other way around.Methods:As proof‐of‐principle, a reconstruction algorithm is designed to produce FGCT images. Using simulated detector data, voxels intersecting a line drawn between the radiation source and an individual detector are traced and modified using the detector signal. The detector signal is modified to compensate for changes in the source to detector distance. Adjacent voxels are modified in proportion to the detector signal, providing a simple image filter.Results:Image‐quality from the proposed FGCT reconstruction technique is proving to be a challenge, producing hardily recognizable images from limited projections angles.Conclusion:Preliminary assessment of the reconstruction technique demonstrates the inevitable tradeoff of producing meaningful image‐quality verses the practicality of how to obtain sufficient image data.

4D CITY TRANSFORMATIONS BY TIME SERIES OF AERIAL IMAGES

Abstract. Recent photogrammetric applications, based on dense image matching algorithms, allow to use not only images acquired by digital cameras, amateur or not, but also to recover the vast heritage of analogue photographs. This possibility opens up many possibilities in the use and enhancement of existing photos heritage. The research of the original figuration of old buildings, the virtual reconstruction of disappeared architectures and the study of urban development are some of the application areas that exploit the great cultural heritage of photography. Nevertheless there are some restrictions in the use of historical images for automatic reconstruction of buildings such as image quality, availability of camera parameters and ineffective geometry of image acquisition. These constrains are very hard to solve and it is difficult to discover good dataset in the case of terrestrial close range photogrammetry for the above reasons. Even the photographic archives of museums and superintendence, while retaining a wealth of documentation, have no dataset for a dense image matching approach. Compared to the vast collection of historical photos, the class of aerial photos meets both criteria stated above. In this paper historical aerial photographs are used with dense image matching algorithms to realize 3d models of a city in different years. The models can be used to study the urban development of the city and its changes through time. The application relates to the city centre of Verona, for which some time series of aerial photographs have been retrieved. The models obtained in this way allowed, right away, to observe the urban development of the city, the places of expansion and new urban areas. But a more interesting aspect emerged from the analytical comparison between models. The difference, as the Euclidean distance, between two models gives information about new buildings or demolitions. As considering accuracy it is necessary point out that the quality of final observations from model comparison depends on several aspects such as image quality, image scale and marker accuracy from cartography.

Measuring glacier surface roughness using plot-scale, close-range digital photogrammetry

AbstractGlacier roughness at sub-metre scales is an important control on the ice surface energy balance and has implications for scattering energy measured by remote-sensing instruments. Ice surface roughness is dynamic as a consequence of spatial and temporal variation in ablation. To date, studies relying on singular and/or spatially discrete two-dimensional profiles to describe ice surface roughness have failed to resolve common patterns or causes of variation in glacier surface morphology. Here we demonstrate the potential of close-range digital photogrammetry as a rapid and cost-effective method to retrieve three-dimensional data detailing plot-scale supraglacial topography. The photogrammetric approach here employed a calibrated, consumer-grade 5 Mpix digital camera repeatedly imaging a plot-scale (≤25 m2) ice surface area on Midtre Lovénbreen, Svalbard. From stereo-pair images, digital surface models (DSMs) with sub-centimetre horizontal resolution and 3 mm vertical precision were achieved at plot scales ≤4 m2. Extraction of roughness metrics including estimates of aerodynamic roughness length (z0) was readily achievable, and temporal variations in the glacier surface topography were captured. Close-range photogrammetry, with appropriate camera calibration and image acquisition geometry, is shown to be a robust method to record sub-centimetre variations in ablating ice topography. While the DSM plot area may be limited through use of stereo-pair images and issues of obliquity, emerging photogrammetric packages are likely to overcome such limitations.