scholarly journals A Rapid UAV Image Georeference Algorithm Developed for Emergency Response

2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Shumin Wang ◽  
Ling Ding ◽  
Zihan Chen ◽  
Aixia Dou
Keyword(s):  
Feature Matching ◽  
Image Data ◽  
Image Rotation ◽  
3D Model Reconstruction ◽  
The World ◽  
Aerial Vehicle ◽  
Left Corner ◽  
Uav Images ◽  
Uav Image ◽  
Image Collection

The image collection system based on the unmanned aerial vehicle plays an important role in the postearthquake response and disaster investigation. In the postearthquake response period, for hundreds of image stitching or 3D model reconstruction, the traditional UAV image processing methods may take one or several hours, which need to be improved on the efficiency. To solve this problem, the UAV image rapid georeference method for postearthquake is proposed in this paper. Firstly, we discuss the rapid georeference model of UAV images and then adopt the world file designed and developed by ESRI to organize the georeferenced image data. Next, the direct georeference method based on the position and attitude data collected by the autopilot system is employed to compute the upper-left corner coordinates of the georeferenced images. For the differences of image rotation manners between the rapid georeference model and the world file, the rapid georeference error compensation model from the image rotation is considered in this paper. Finally, feature extraction and feature matching for UAV images and referenced image are used to improve the accuracy of the position parameters in the world file, which will reduce the systematic error of the georeferenced images. We use the UAV images collected from Danling County and Beichuan County, Sichuan Province, to implement the rapid georeference experiments employing different types of UAV. All the images are georeferenced within three minutes. The results show that the algorithm proposed in this paper satisfies the time and accuracy requirements of postearthquake response, which has an important application value.

scholarly journals Fast Anchor Point Matching for Emergency UAV Image Stitching Using Position and Pose Information

Sensors ◽  
2020 ◽  
Vol 20 (7) ◽  
pp. 2007
Author(s):  
Ruizhe Shao ◽  
Chun Du ◽  
Hao Chen ◽  
Jun Li
Keyword(s):  
Image Stitching ◽  
Feature Points ◽  
Point Matching ◽  
Novel Approach ◽  
Aerial Vehicle ◽  
Speed Up ◽  
Anchor Points ◽  
Uav Images ◽  
Uav Image ◽  
Traditional Approaches

With the development of unmanned aerial vehicle (UAV) techniques, UAV images are becoming more widely used. However, as an essential step of UAV image application, the computation of stitching remains time intensive, especially for emergency applications. Addressing this issue, we propose a novel approach to use the position and pose information of UAV images to speed up the process of image stitching, called FUIS (fast UAV image stitching). This stitches images by feature points. However, unlike traditional approaches, our approach rapidly finds several anchor-matches instead of a lot of feature matches to stitch the image. Firstly, from a large number of feature points, we design a method to select a small number of them that are more helpful for stitching as anchor points. Then, a method is proposed to more quickly and accurately match these anchor points, using position and pose information. Experiments show that our method significantly reduces the time consumption compared with the-state-of-art approaches with accuracy guaranteed.

scholarly journals Efficient SfM for Oblique UAV Images: From Match Pair Selection to Geometrical Verification

2018 ◽  
Vol 10 (8) ◽  
pp. 1246 ◽  
Author(s):  
San Jiang ◽  
Wanshou Jiang
Keyword(s):  
Feature Matching ◽  
Bundle Adjustment ◽  
Imaging Systems ◽  
Match Pair ◽  
Software Packages ◽  
Aerial Vehicle ◽  
Selection For ◽  
Image Pairs ◽  
Uav Images ◽  
Reliable Solution

Accurate orientation is required for the applications of UAV (Unmanned Aerial Vehicle) images. In this study, an integrated Structure from Motion (SfM) solution is proposed, which aims to address three issues to ensure the efficient and reliable orientation of oblique UAV images, including match pair selection for large-volume images with large overlap degree, reliable feature matching of images captured from varying directions, and efficient geometrical verification of initial matches. By using four datasets captured with different oblique imaging systems, the proposed SfM solution is comprehensively compared and analyzed. The results demonstrate that linear computational costs can be achieved in feature extraction and matching; although high decrease ratios occur in image pairs, reliable orientation results are still obtained from both the relative and absolute bundle adjustment (BA) tests when compared with other software packages. For the orientation of oblique UAV images, the proposed method can be an efficient and reliable solution.

scholarly journals Object Segmentation on UAV Photo Data to Support the Provision of Rural Area Spatial Information

2015 ◽  
Vol 29 (1) ◽  
Author(s):  
Nurwita Mustika Sari ◽  
Dony Kushardono
Keyword(s):  
Rural Area ◽  
Rural Areas ◽  
Spatial Information ◽  
Remote Sensing Data ◽  
Image Data ◽  
Aerial Photographs ◽  
Segmentation Method ◽  
Object Based ◽  
Aerial Vehicle ◽  
Uav Image

The use of Unmanned Aerial Vehicle (UAV) to take aerial photographs is increasing in recent years. Photo data taken by UAV become one of reliable detailed-scale  remote sensing data sources. The capability to obtain cloud-free images and the flexibility of time are some of the advantages of UAV photo data compared to satellite images with optical sensor. Displayed area at the data shows the objects clearly. Rural area has certain characteristics in its land cover namely ricefield. To delineate the area correctly there is an object-based image analysis methods (OBIA) that could be applied. In this  study, proposed a novel method to  execute the separation of objects that exist in the data with segmentation method. The result shows an effective segmentation method to separate different objects in rural areas recorded on UAV image data. The accuracy obtained is 90.47% after optimization process. This segmentation can be a valid basis to support the provision of spatial information in rural area.

scholarly journals Coral Reef Mapping of UAV: A Comparison of Sun Glint Correction Methods

2019 ◽  
Vol 11 (20) ◽  
pp. 2422 ◽  
Author(s):  
Muslim ◽  
Chong ◽  
Safuan ◽  
Khalil ◽  
Hossain
Keyword(s):  
Coral Reef ◽  
Image Data ◽  
Peninsular Malaysia ◽  
Coral Rubble ◽  
Distribution Mapping ◽  
Multi Temporal ◽  
Aerial Vehicle ◽  
Accuracy Result ◽  
Uav Image ◽  
Removal Technique

Although methods were proposed for eliminating sun glint effects from airborne and satellite images over coral reef environments, a method was not proposed previously for unmanned aerial vehicle (UAV) image data. De-glinting in UAV image analysis may improve coral distribution mapping accuracy result compared with an uncorrected image classification technique. The objective of this research was to determine accuracy of coral reef habitat classification maps based on glint correction methods proposed by Lyzenga et al., Joyce, Hedley et al., and Goodman et al.. The UAV imagery collected from the coral-dominated Pulau Bidong (Peninsular Malaysia) on 20 April 2016 was analyzed in this study. Images were pre-processed with the following two strategies: Strategy-1 was the glint removal technique applied to the whole image, while Strategy-2 used only the regions impacted by glint instead of the whole image. Accuracy measures for the glint corrected images showed that the method proposed by Lyzenga et al. following Strategy-2 could eliminate glints over the branching coral—Acropora (BC), tabulate coral—Acropora + Montipora (TC), patch coral (PC), coral rubble (R), and sand (S) with greater accuracy than the other four methods using Strategy-1. Tested in two different coral environments (Site-1: Pantai Pasir Cina and Site-2: Pantai Vietnam), the glint-removed UAV imagery produced reliable maps of coral habitat distribution with finer details. The proposed strategies can potentially be used to remove glint from UAV imagery and may improve usability of glint-affected imagery, for analyzing spatiotemporal changes of coral habitats from multi-temporal UAV imagery.

scholarly journals Automatic Seam-Line Detection in UAV Remote Sensing Image Mosaicking by Use of Graph Cuts

2018 ◽  
Vol 7 (9) ◽  
pp. 361 ◽  
Author(s):  
Ming Li ◽  
Deren Li ◽  
Bingxuan Guo ◽  
Lin Li ◽  
Teng Wu ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Energy Function ◽  
Graph Cuts ◽  
Remote Sensing Image ◽  
Existing Problems ◽  
Image Mosaicking ◽  
Target Energy ◽  
Aerial Vehicle ◽  
Uav Images ◽  
Uav Image

Image mosaicking is one of the key technologies in data processing in the field of computer vision and digital photogrammetry. For the existing problems of seam, pixel aliasing, and ghosting in mosaic images, this paper proposes and implements an optimal seam-line search method based on graph cuts for unmanned aerial vehicle (UAV) remote sensing image mosaicking. This paper first uses a mature and accurate image matching method to register the pre-mosaicked UAV images, and then it marks the source of each pixel in the overlapped area of adjacent images and calculates the energy value contributed by the marker by using the target energy function of graph cuts constructed in this paper. Finally, the optimal seam-line can be obtained by solving the minimum value of target energy function based on graph cuts. The experimental results show that our method can realize seamless UAV image mosaicking, and the image mosaic area transitions naturally.

scholarly journals Assessment of DSM Based on Radiometric Transformation of UAV Data

Sensors ◽  
2021 ◽  
Vol 21 (5) ◽  
pp. 1649
Author(s):  
Muhammad Hamid Chaudhry ◽  
Anuar Ahmad ◽  
Qudsia Gulzar ◽  
Muhammad Shahid Farid ◽  
Himan Shahabi ◽  
...  
Keyword(s):  
Point Cloud ◽  
Accuracy Assessment ◽  
Low Cost ◽  
Image Data ◽  
Flying Height ◽  
Surface Model ◽  
Lidar Data ◽  
Local Accuracy ◽  
Uav Images ◽  
Uav Image

Unmanned Aerial Vehicle (UAV) is one of the latest technologies for high spatial resolution 3D modeling of the Earth. The objectives of this study are to assess low-cost UAV data using image radiometric transformation techniques and investigate its effects on global and local accuracy of the Digital Surface Model (DSM). This research uses UAV Light Detection and Ranging (LIDAR) data from 80 meters and UAV Drone data from 300 and 500 meters flying height. RAW UAV images acquired from 500 meters flying height are radiometrically transformed in Matrix Laboratory (MATLAB). UAV images from 300 meters flying height are processed for the generation of 3D point cloud and DSM in Pix4D Mapper. UAV LIDAR data are used for the acquisition of Ground Control Points (GCP) and accuracy assessment of UAV Image data products. Accuracy of enhanced DSM with DSM generated from 300 meters flight height were analyzed for point cloud number, density and distribution. Root Mean Square Error (RMSE) value of Z is enhanced from ±2.15 meters to 0.11 meters. For local accuracy assessment of DSM, four different types of land covers are statistically compared with UAV LIDAR resulting in compatibility of enhancement technique with UAV LIDAR accuracy.

scholarly journals Automatic UAV Image Geo-Registration by Matching UAV Images to Georeferenced Image Data

2017 ◽  
Vol 9 (4) ◽  
pp. 376 ◽  
Author(s):  
Xiangyu Zhuo ◽  
Tobias Koch ◽  
Franz Kurz ◽  
Friedrich Fraundorfer ◽  
Peter Reinartz
Keyword(s):  
Image Data ◽  
Uav Images ◽  
Uav Image

scholarly journals A Robust Method for Automatic Panoramic UAV Image Mosaic

Sensors ◽  
2019 ◽  
Vol 19 (8) ◽  
pp. 1898 ◽  
Author(s):  
Jun Chen ◽  
Quan Xu ◽  
Linbo Luo ◽  
Yongtao Wang ◽  
Shuchun Wang
Keyword(s):  
Remote Sensing ◽  
Feature Matching ◽  
Bundle Adjustment ◽  
Image Mosaic ◽  
Robust Method ◽  
Remote Sensing Images ◽  
Ideal Situation ◽  
New Strategy ◽  
Aerial Vehicle ◽  
Uav Image

This paper introduces a robust method for panoramic unmanned aerial vehicle (UAV) image mosaic. In the traditional automatic panoramic image stitching method (Autostitch), it assumes that the camera rotates about its optical centre and the group of transformations the source images may undergo is a special group of homographies. It is rare to get such ideal data in reality. In particular, remote sensing images obtained by UAV do not satisfy such an ideal situation, where the images may not be on a plane yet and even may suffer from nonrigid changes, leading to poor mosaic results. To overcome the above mentioned challenges, in this paper a nonrigid matching algorithm is introduced to the mosaic system to generate accurate feature matching on remote sensing images. We also propose a new strategy for bundle adjustment to make the mosaic system suitable for the UAV image panoramic mosaic effect. Experimental results show that our method outperforms the traditional method and some of the latest methods in terms of visual effect.

scholarly journals Research on application of Unmanned Aerial Vehicles (UAVs) in cadastral mapping of arable land

2020 ◽  
Vol 61 (5) ◽  
pp. 43-53
Author(s):  
Quy Ngoc Bui ◽  
Tuan Anh Pham ◽  
Quan Anh Duong ◽  
Hiep Van Pham ◽  
Kien Trung Tran ◽  
...  
Keyword(s):  
Agricultural Land ◽  
Arable Land ◽  
Image Data ◽  
Land Administration ◽  
Cadastral Maps ◽  
Average Accuracy ◽  
Land Surveying ◽  
Uav Images ◽  
Uav Image ◽  
Research On Application

Cadastral maps are an important part of cadastral documents, they are legal component of land administration in local authorities. Traditionally, a cadastral map is established by using land surveying methods which can provide high accuracy as required. In recent years, the UAV devices are developed and can provide an accurately tool for cadastral mapping on arable lands. This paper presents an evaluation of UAV application in cadastral mapping in comparison with traditional surveying for arable land. The results show that using UAV images in the mapping of agricultural land can achieve ground accuracy of 1,7 cm and height accuracy of 0,6 cm; In addition, when comparing the average accuracy of the 30 plot vertices and the mean lengths from 29 pairs of edges between the newly created map from the UAV image data and the map provided by the Department of Natural Resources and Environment of Phu Tho province, respectively is: 0,181 m and: 0,051 m.

scholarly journals Building DEM for deep open-pit coal mines using DJI Inspire 2

2020 ◽  
Vol 61 (1) ◽  
pp. 1-10
Author(s):  
Nguyen Viet Nghia ◽  
Keyword(s):  
3D Model ◽  
Coal Mines ◽  
Image Data ◽  
Maximum Error ◽  
3D Models ◽  
Reference Points ◽  
Open Pit ◽  
Open Pit Mines ◽  
Aerial Vehicle ◽  
Uav Image

Using photo data of unmanned aerial vehicle (UAV) for building 3D models has been widely used in recent years. However, building a 3D model for deep open - pit coal mines with the mean height difference between surface and bottom of mines to over 500 m, there has not been researched mentioned. The paper deals with the assessment possibility of developing 3D models for deep open - pit mines from UAV image data. To accomplish this goal, DJI's Inspire 2 flying device is used to take the photo at Coc Sau coal mine. The flying area is 4 km2, the flight altitude compared to the takeoff point on the mine surface is 250 m, the overlaying coverage is both horizontal and vertical is 70%. The average errors of the horizontal and height elements of the reference points photo correlates are 0.011 m, 0.017 m, 0.016 m, 0.049 m, and 0.051 m. The maximum error on the X-axis is - 0,025 m, and the Y-axis is 0.028 m, the maximum horizontal error is 0.034 m, the maximum error on the Z-axis is 0.095 m, and the position error is 0.095 m. These results show that the 3D model established from photographic data by Inspire 2 device has satisfied the requirements of the accuracy of establishing the mining terrain map 1: 1000 scale.

Sign in / Sign up

Export Citation Format

Share Document