Image Resolution Requirements Research Articles

UAV Velocity Function Design and Trajectory Planning for Heterogeneous Visual Coverage of Terrestrial Regions

In this paper, we propose a novel approach of designing the velocity function and the trajectory for a UAV to efficiently achieve location-dependent visual coverage. Specifically, the UAV dynamically adjusts its altitude to photograph terrestrial polygons with different image resolution requirements. Unlike prior work that assumes the UAV speed is constant, the proposed approach allows the UAV to change its speed. To minimize the task completion time, we put forward a novel approach that is composed of three algorithmic components. The first component uses an aggressive method for selecting the UAV photographing altitudes, designs the UAV velocity functions, and derives the UAV flying times for all pairs of regions. Based on the UAV flying times rather than the distances, the second component utilizes an auxiliary traveling salesman problem to determine the visited order of terrestrial regions. For each terrestrial region, the third component generates candidate coverage paths and picks up the coverage path based on the UAV flying time. We also derive analytical results on the UAV trajectory length. Large-scale simulation results indicate that the proposed approach outperforms a two-dimensional trajectory planning algorithm and a greedy algorithm for planning a three-dimensional trajectory in terms of the UAV task completion time.

UAV Placement for VR Reconstruction: A Tradeoff Between Resolution and Delay

Unmanned aerial vehicle (UAV) can be combined with virtual reality (VR) to collect the rapidly changing physical environment by leveraging its high flexibility, so as to provide an immersive experience for metaverse users. In this letter, we study the UAV placement problem in UAV-assisted VR systems where UAVs are deployed to capture images of ground targets and then transmit them to ground users for virtual environment reconstruction. The goal is to minimize the transmission delay while satisfying the image resolution requirement. Firstly, the UAV placement problem is formulated into a non-convex optimization problem. Then, an efficient algorithm is proposed to obtain a high-quality solution by adopting the block coordinate descent and successive convex approximation techniques with low complexity. Finally, the numerical results are provided and show that considerable benefits can be obtained with a suboptimal UAV placement. Specifically, the proposed scheme can reduce the transmission delay by over 15 ms compared to the conventional scheme when the received signal-to-noise ratio at the reference distance is 10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">6</sup> and the resolution requirement is 0.5.

Emerging Technologies for Advanced 3D Package Characterization to Enable the More-Than-Moore Era

The line between packaging and silicon interconnect technology is blurring due to a reduction in package interconnect dimensions, which drives an increase in image resolution requirements. It is becoming more difficult to localize and image defects and structures throughout the packaging life cycle, from materials selection, through package and silicon design co-optimization, development, production, and field failure diagnostics. Characterization and failure analysis (FA) solutions must provide fast results for rapid development of packages meeting the required electrical, mechanical and reliability specifications with high yield and quality. Heterogeneous integration and complex packages containing multiple die drive new approaches to rapidly characterize structures, defects and processes. This paper presents new artificial intelligence (AI) developments in 3D X-ray microscopy (XRM) for non-destructive submicron-resolution imaging of packages. It also introduces the latest developments in focused ion beam (FIB) microscopes adapted with an integrated fs-laser for precise and fast analysis of deeply buried features in advanced packages.

Photographing Alopecia: How Many Pixels Are Needed for Clinical Evaluation?

Determining the minimum image resolution needed for clinical assessment is crucial for computational efficiency, image standardization, and storage needs alleviation. In this paper, we explore the image resolution requirements for the assessment of alopecia by analyzing how clinicians detect the presence of characteristics needed to quantify the disorder in the clinic. By setting the image resolution as a function of width of the patient's head, we mimicked experiments conducted in the computer vision field to understand human perception in the context of scene recognition and object detection and asked 6 clinicians to identify the regions of interest on a set of retrospectively collected de-identified images at different resolutions. The experts were able to detect the presence of alopecia at very low resolutions, while significantly higher resolution was required to identify the presence of vellus-like hair. Furthermore, the accuracy with which alopecia was detected as a function of resolution followed the same trend as the one obtained when we classified normal versus abnormal hair density using a standard neural network architecture, hinting that the resolution needed by an expert human observer may also provide an upper bound for future image processing algorithms.

Development of a low-cost imaging system for remote mosquito surveillance.

Targeted vector control strategies aiming to prevent mosquito borne disease are severely limited by the logistical burden of vector surveillance, the monitoring of an area to understand mosquito species composition, abundance and spatial distribution. We describe development of an imaging system within a mosquito trap to remotely identify caught mosquitoes, including selection of the image resolution requirement, a design to meet that specification, and evaluation of the system. The necessary trap image resolution was determined to be 16 lp/mm, or 31.25um. An optics system meeting these specifications was implemented in a BG-GAT mosquito trap. Its ability to provide images suitable for accurate specimen identification was evaluated by providing entomologists with images of individual specimens, taken either with a microscope or within the trap and asking them to provide a species identification, then comparing these results. No difference in identification accuracy between the microscope and the trap images was found; however, due to limitations of human species classification from a single image, the system is only able to provide accurate genus-level mosquito classification. Further integration of this system with machine learning computer vision algorithms has the potential to provide near-real time mosquito surveillance data at the species level.

Area-Based Dense Image Matching with Subpixel Accuracy for Remote Sensing Applications: Practical Analysis and Comparative Study

Dense image matching is a crucial step in many image processing tasks. Subpixel accuracy and fractional measurement are commonly pursued, considering the image resolution and application requirement, especially in the field of remote sensing. In this study, we conducted a practical analysis and comparative study on area-based dense image matching with subpixel accuracy for remote sensing applications, with a specific focus on the subpixel capability and robustness. Twelve representative matching algorithms with two types of correlation-based similarity measures and seven types of subpixel methods were selected. The existing matching algorithms were compared and evaluated in a simulated experiment using synthetic image pairs with varying amounts of aliasing and two real applications of attitude jitter detection and disparity estimation. The experimental results indicate that there are two types of systematic errors: displacement-dependent errors, depending on the fractional values of displacement, and displacement-independent errors represented as unexpected wave artifacts in this study. In addition, the strengths and limitations of different matching algorithms on the robustness to these two types of systematic errors were investigated and discussed.

Palmprint Image Acquisition and Analysis System Based on IoT Technology

With the rapid development and advancement of society, information technology represented by biometric recognition has developed rapidly. Palmprint images have a larger area, more texture details, rich texture features and distinguishable information, and palmprint recognition is opposite to the palm. The pattern image acquisition equipment and resolution requirements are not high, which is suitable for palmprint image acquisition and analysis under the framework of the Internet of Things (IoT), and then realize the design of recognition technology and system based on palmprint texture characteristics. The palmprint texture feature extraction and analysis algorithm is deployed on the cloud server, and the analysis result is fed back to the on-site collection device to realize the collection and analysis of palmprint images.

Image-Based Quantitative Analysis of Foxing Stains on Old Printed Paper Documents

We studied the feasibility of image-based quantitative analysis of foxing stains on collections of old (16th–20th century) European books stored in the Rare Book Library of the Seoul National University in Korea. We were able to quantitatively determine the foxing affected areas on books from their photographs using a newly developed image processing software (PicMan) including cultural property characterization applications, specifically. Dimensional and color analysis of photographs were successfully done quantitatively. Histograms of RGB (red, green, blue) pixels of photographs clearly showed the change in color distribution of foxing stains compared to the other areas of the photographs. Several sample images of quantitative measurement of foxing stains and virtually restored images were generated to provide easy visual inspection and comparison between restored images and the original photographs. Image quality, resolution, and digital file format requirements for quantitative analysis are described. Image-based quantitative analysis of foxing stains on paper documents are found to be very promising towards automation for objective characterization of photographs of cultural properties. This technique can be used to create a cultural property digital database. Quantitative and statistical analysis techniques can be introduced to monitor the effect of storage and conservation environment on the cultural properties.

3D printing with MRI in pediatric applications.

3D printing (3DP) applications for clinical evaluation, preoperative planning, patient and trainee education, and simulation has increased in the past decade. Most of the applications are found in cardiovascular, head and neck, orthopedic, neurological, urological, and oncological surgical cases. This review has three parts. The first part discusses the technical pathway to realizing a physical model, 3DP considerations in pediatric MRI image acquisition, data and resolution requirements, and related structural segmentation and postprocessing steps needed to generalize both virtual and physical models. Standard practices and processing software used in these processes will be assessed. The second part discusses complementary examples in pediatric applications, including cases from cardiology, neuroradiology, neurology, and neurosurgery, head and neck, orthopedics, pelvic and urological applications, oncological applications, and fetal imaging. The third part explores other 3D printing applications and considerations such as using 3DP to develop tissue-specific phantoms and devices for testing in the MR environment, to educate patients and their families, to train clinicians and students, and facility requirements for building a 3DP program. Level of Evidence: 5 Technical Efficacy: Stage 5 J. Magn. Reson. Imaging 2020;51:1641-1658.

Manoeuvring target motion parameter estimation for ISAR image fusion

In inverse synthetic aperture radar (ISAR) imaging applications, generating an image of a manoeuvring target is a challenge due to the tradeoff between the fine image resolution requirements and the temporal variability of the Doppler response. The time frequency transform (TFT) is a common method to solve this problem. Prior TFT-based research assumes that the ISAR observes the target from a single fixed aspect. Because of its manoeuvring characteristics, the target motion features are sometimes not extractable from the observing aspect, but become much more distinct from other aspects. ISAR image fusion is thus able to provide significant advantages, since multiple looks of the same target from different aspects will increase the available knowledge. After constructing the common projection plane and building up the physical connection between radars and the manoeuvring target, the parameters that describe the target motion are estimated for very short time duration within which the Doppler response can be assumed to be a constant. Simulation results confirm the effectiveness of the estimation procedure and thus the fusion method. The authors conclude that the ISAR system must be carefully configured in order to realise the full benefits of their image fusion technique for manoeuvring targets.

Intelligent video display can improve visual detail and quality on mobile devices

Although multifunctional hand-held devices are proliferating rapidly, for reasons of cost they generally feature video services that merely offer resized content for mobile consumption. Experiments to assess image resolution and bit-rate requirements indicate that the primary defect of the reduced image resolution is loss of visual detail. Field sports are more problematic than music, news, and animation. Soccer, one of the most popular broadcast sports (see Figure 1), is a prime example. For some types of content, an intelligent display scheme would generate a magnified view of regions of interest (ROIs), defined as some portion of a scene to which the viewer will pay special attention. Determining ROIs is valuable for contextaware content adaptation, transcoding, and intelligent information management. In addition, it can serve as a first step to semantic-level interpretation. Instead of traditional visual salience orientation, we employ a domain-specific approach to exploit the particular attributes of soccer video. We distinguish between the various camera angles and the long shot, in which the ball and players are tiny when viewed on a small display, as in Figure 2(a). The scene would be more readily understood if an ROI were extracted and magnified. Other frames, whether mid-shots or close-ups, are easily understood: see Figure 2(b) and (c). Thus, for improved display on a small LCD panel, the frames can be sorted into just two categories, and only a part of a whole image need be extracted from the long-shot frames.

Clinical applications of picture archival and communications systems in radiation oncology

Picture archival and communications systems (PACS) for radiation oncology present an entirely different set of constraints and requirements from systems developed for diagnostic imaging. PACS for radiation oncology aid in organizing the complex, interrelated functions of radiation oncology. Integration of PACS with clinical data management systems will provide the backbone for the comprehensive computer system that has long been sought in radiation oncology. Simulation, geometric and dosimetric treatment planning, field shaping, set-up, verification, and delivery are now all observable and/or controllable from computer systems that can be interfaced with the departmental PACS. Costs are substantially lower than with diagnostic PACS because the systems can be based on desktop computers and the image resolution requirements are not as stringent. Each PACS user will have more information more easily available than under current systems of organization. Vendor support of digital image communications (DICOM) protocols will enable full integration of equipment regardless of manufacturer. Potential increased in productivity will be realized if the systems for handling and evaluating images are fully automated and provide the users with analytic tools that enhance the utility of systems such as electronic portal imagers, multileaf collimators, and clinical data management systems. this report describes our efforts in producing such a system.

Prediction of SAR focus performance using ephemeris covariance

Synthetic-aperture radar (SAR) focus can be achieved based on either accurate ephemeris data or SAR processing parameters obtained from an autofocus process. For an SAR mapping project, a decision to choose one approach must be made in the early phase of system design. This requires a detailed analysis to predict the focus performance based on the predicted performance of the ephemeris data. For the Magellan project, this analysis is complicated by the facts that the Magellan radar is operated in a burst mode, and the Magellan radar maps the surface of Venus from a highly elliptical orbit. An analysis that is general enough so that both the strip mapping mode SAR system and the burst mode SAR system are considered is presented. The final result indicates that the ephemeris data obtained from the Magellan navigation system provides sufficient accuracy for meeting the Magellan image resolution requirement. >

Rainbow holographic aberrations and the bandwidth requirements

Rainbow holographic image resolution, primary aberrations, and bandwidth requirements are presented. The results obtained for the rainbow holographic process are rather general, for which the conventional holographic image resolution, aberrations, and bandwidth requirements, can be derived. The conditions for the elimination of the five primary rainbow holographic aberrations are also given. These conditions may be useful for the application of obtaining a high-quality rainbow hologram image. In terms of bandwidth requirements, we have shown that the bandwidth requirement for a rainbow holographic construction is usually several orders lower than that of a conventional holographic process. Therefore, a lower-resolution recording medium can generally be used for most of the rainbow holographic constructions.

Infrared Zoom Lens System For Target Detection

A conceptually simple high speed infrared (IR) zoom lens system has been designed to operate in the 8 to 13µm wavelength region for the detection of missile signatures. Even though the optical system is designed to provide high resolution throughout the 3:1 zoom range at a large relative aperture, it is extremely lightweight and compact. The zoom concept has been derived from first-order optical principles which will be presented as the starting point of the optical system design. The use of the symmetry principle for aberration correction will be discussed. Paraxial ray trace was used as an aid in establishing lens powers and groupings in the initial layout. Considerations which governed material selection will also be discussed. The zoom system consists of six lens elements including a field flattener near the image plane. The total glass weight is only 172.4 grams and the length is 161.79 mm. There are two moving lens components linked together with a cam to provide mechanical compensation. The detail design was accomplished through the use of a computer optimization program. The 1 mrad image resolution requirement is achieved throughout the zoom range. Performance data will be presented and tolerance considerations will be discussed.

Stereoscopic Methods in TEM

The use of stereoscopy to characterize three-dimensional structures observed by TEM has become widespread since the introduction of instruments operating at 1 MV. In its emphasis on whole structures and thick specimens this approach differs significantly from conventional methods of microstructural analysis based on three-dimensional image reconstruction from a number of thin-section views. The great advantage of stereo derives from the ability to directly perceive and measure structures in three-dimensions by capitalizing on the unsurpassed human ability for stereoscopic matching of corresponding details on picture pairs showing the same features from different viewpoints. At this time, stereo methods are aimed mainly at structural understanding at the level of dislocations, precipitates and irradiation-induced point-defect clusters in crystal and on the cellular level of biological specimens. 3-d reconstruction methods have concentrated on the molecular level where image resolution requirements dictate the use of very thin specimens.For the most part the stereo methods used in TEM are direct and unsophisticated. Stereo pairs of micrographs are taken by tilting the specimen to record two views of the same structural features from viewpoints ten or so degrees apart.