scholarly journals High-Resolution Image Transmission from UAV to Ground Station for Search and Rescue Missions Planning

2021 ◽  
Vol 11 (5) ◽  
pp. 2105
Author(s):  
Vladan Papić ◽  
Petar Šolić ◽  
Ante Milan ◽  
Sven Gotovac ◽  
Miljenko Polić
Keyword(s):  
High Resolution ◽  
Real Time ◽  
Image Transmission ◽  
Search And Rescue ◽  
Aerial Images ◽  
Ground Station ◽  
Transmission Distance ◽  
Aerial Vehicle ◽  
High Resolution Images ◽  
Future Work

Search and rescue (SAR) missions comprise search for, and provision of aid to people who are in distress or imminent danger. Providing the best possible input for the planners and search teams, up-to-date information about the terrain is of essential importance because every additional hour needed to search a person decreases probability of success. Therefore, availability of aerial images and updated terrain maps as a basis for planning and monitoring SAR missions in real-time is very important for rescuers. In this paper, we present a system for transmission of high-resolution images from an unmanned aerial vehicle (UAV) to the ground station (GS). We define and calculate data rate and transmission distance requirements between the UAV and GS in a mission scenario. Five tests were designed and carried out to confirm the viability of the proposed system architecture and modules. Test results present throughput measurements for various UAV and GS distances, antenna heights and UAV antenna yaw angles. Experimental results from the series of conducted outdoor tests show that the proposed solution using two pMDDL2450 datalinks at 2.4 GHz and a directional antenna on the receiving side can be used for a real-time transmission of high-resolution images acquired with a camera on a UAV. Achieved throughput at a UAV-GS distance of 5 km was 1.4 MB/s (11.2 Mbps). The limitations and possible improvements of the proposed system as well as future work are also discussed.

Electrical Probing and Surface Imaging of Deep Sub-Micron Integrated Circuits

1999 ◽  
Author(s):  
Kenneth Krieg ◽  
Richard Qi ◽  
Douglas Thomson ◽  
Greg Bridges
Keyword(s):  
High Resolution ◽  
Integrated Circuits ◽  
Real Time ◽  
High Speed ◽  
Time Signal ◽  
Surface Imaging ◽  
Atomic Force ◽  
Submicron Structures ◽  
High Resolution Images ◽  
Capacitive Loading

Abstract A contact probing system for surface imaging and real-time signal measurement of deep sub-micron integrated circuits is discussed. The probe fits on a standard probe-station and utilizes a conductive atomic force microscope tip to rapidly measure the surface topography and acquire real-time highfrequency signals from features as small as 0.18 micron. The micromachined probe structure minimizes parasitic coupling and the probe achieves a bandwidth greater than 3 GHz, with a capacitive loading of less than 120 fF. High-resolution images of submicron structures and waveforms acquired from high-speed devices are presented.

Real-time, parallel segmentation of high-resolution images on multi-core platforms

2014 ◽  
Vol 13 (4) ◽  
pp. 685-702 ◽  
Author(s):  
Dana Forsthoefel Fitzgerald ◽  
D. Scott Wills ◽  
Linda M. Wills
Keyword(s):  
High Resolution ◽  
Real Time ◽  
High Resolution Images

scholarly journals Utilizing drone technology in the civil engineering

2019 ◽  
Vol 14 (1) ◽  
pp. 27-37
Author(s):  
Matúš Tkáč ◽  
Peter Mésároš
Keyword(s):  
Real Time ◽  
Unmanned Aerial Vehicle ◽  
Civil Engineering ◽  
Aerial Images ◽  
General Overview ◽  
Aerial Photogrammetry ◽  
Different Types ◽  
Aerial Vehicle

Abstract An unmanned aerial vehicle (UAVs), also known as drone technology, is used for different types of application in the civil engineering. Drones as a tools that increase communication between construction participants, improves site safety, uses topographic measurements of large areas, with using principles of aerial photogrammetry is possible to create buildings aerial surveying, bridges, roads, highways, saves project time and costs, etc. The use of UAVs in the civil engineering can brings many benefits; creating real-time aerial images from the building objects, overviews reveal assets and challenges, as well as the broad lay of the land, operators can share the imaging with personnel on site, in headquarters and with sub-contractors, planners can meet virtually to discuss project timing, equipment needs and challenges presented by the terrain. The aim of this contribution is to create a general overview of the use of UAVs in the civil engineering. The contribution also contains types of UAVs used for construction purposes, their advantages and also disadvantages.

Infrastructure Inspection Using an Unmanned Aerial System (UAS) With Metamodeling-Based Image Correction

2016 ◽  
Author(s):  
Chen-Ming Kuo ◽  
Chung-Hsin Kuo ◽  
Shu-Ping Lin ◽  
Mark Christian E. Manuel ◽  
Po Ting Lin ◽  
...  
Keyword(s):  
High Resolution ◽  
Ccd Camera ◽  
Kriging Model ◽  
Image Correction ◽  
Railway Transport ◽  
Truss Bridges ◽  
Aerial Vehicle ◽  
High Resolution Images ◽  
Infrastructure Inspection ◽  
Steel Truss Bridges

Public infrastructures such as bridges are common civil structures for road and railway transport. In Poland, many of the steel truss bridges were constructed in the 1950s or earlier. The aging managements and damage assessments are required to ensure safe operations of these old bridges. The first step of damage assessment is usually done via visual inspection. The said inspection procedure can be expensive, laborious and dangerous as it is often performed by trained personnel. As a solution to this, we have developed and used a custom-designed, modular aerial robot equipped with a CCD camera for the collection of high-resolution images. The images were merged into one single, high-resolution facade map that will be the basis for subsequent evaluation by bridge inspectors. It was observed that the collected images had encountered irregularities which decreases the reliability of the facade map. We have conducted experiments to estimate the correction of image perspective in terms of attitude and position of unmanned aerial vehicle (UAV). A Kriging model was utilized to parametrically model the aforementioned nonlinear relationship. The image reliability is then evaluated based on the variance of the parametric model. The generated information is further used for high fidelity automated image correction and stitching.

scholarly journals Real-Time Moving Object Detection in High-Resolution Video Sensing

Sensors ◽  
2020 ◽  
Vol 20 (12) ◽  
pp. 3591 ◽  
Author(s):  
Haidi Zhu ◽  
Haoran Wei ◽  
Baoqing Li ◽  
Xiaobing Yuan ◽  
Nasser Kehtarnavaz
Keyword(s):  
High Resolution ◽  
Object Detection ◽  
Real Time ◽  
Moving Object Detection ◽  
Moving Object ◽  
Computationally Efficient ◽  
Real Time Processing ◽  
Time Processing ◽  
Video Frames ◽  
High Resolution Images

This paper addresses real-time moving object detection with high accuracy in high-resolution video frames. A previously developed framework for moving object detection is modified to enable real-time processing of high-resolution images. First, a computationally efficient method is employed, which detects moving regions on a resized image while maintaining moving regions on the original image with mapping coordinates. Second, a light backbone deep neural network in place of a more complex one is utilized. Third, the focal loss function is employed to alleviate the imbalance between positive and negative samples. The results of the extensive experimentations conducted indicate that the modified framework developed in this paper achieves a processing rate of 21 frames per second with 86.15% accuracy on the dataset SimitMovingDataset, which contains high-resolution images of the size 1920 × 1080.

scholarly journals DisCountNet: Discriminating and Counting Network for Real-Time Counting and Localization of Sparse Objects in High-Resolution UAV Imagery

2019 ◽  
Vol 11 (9) ◽  
pp. 1128 ◽  
Author(s):  
Maryam Rahnemoonfar ◽  
Dugan Dobbs ◽  
Masoud Yari ◽  
Michael J. Starek
Keyword(s):  
High Resolution ◽  
Real Time ◽  
State Of The Art ◽  
Sparse Matrix ◽  
Aerial Images ◽  
Heat Map ◽  
High Resolution Image ◽  
Current State ◽  
Density Map ◽  
Distinct Features

Recent deep-learning counting techniques revolve around two distinct features of data—sparse data, which favors detection networks, or dense data where density map networks are used. Both techniques fail to address a third scenario, where dense objects are sparsely located. Raw aerial images represent sparse distributions of data in most situations. To address this issue, we propose a novel and exceedingly portable end-to-end model, DisCountNet, and an example dataset to test it on. DisCountNet is a two-stage network that uses theories from both detection and heat-map networks to provide a simple yet powerful design. The first stage, DiscNet, operates on the theory of coarse detection, but does so by converting a rich and high-resolution image into a sparse representation where only important information is encoded. Following this, CountNet operates on the dense regions of the sparse matrix to generate a density map, which provides fine locations and count predictions on densities of objects. Comparing the proposed network to current state-of-the-art networks, we find that we can maintain competitive performance while using a fraction of the computational complexity, resulting in a real-time solution.

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