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 A review of parallel computing for large-scale remote sensing image mosaicking

2015 ◽  
Vol 18 (2) ◽  
pp. 517-529 ◽  
Author(s):  
Lajiao Chen ◽  
Yan Ma ◽  
Peng Liu ◽  
Jingbo Wei ◽  
Wei Jie ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Parallel Computing ◽  
Large Scale ◽  
Remote Sensing Image ◽  
Image Mosaicking

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.

Remote Sensing Image Mosaicking: Achievements and Challenges

2019 ◽  
Vol 7 (4) ◽  
pp. 8-22 ◽  
Author(s):  
Xinghua Li ◽  
Ruitao Feng ◽  
Xiaobin Guan ◽  
Huanfeng Shen ◽  
Liangpei Zhang
Keyword(s):  
Remote Sensing ◽  
Remote Sensing Image ◽  
Image Mosaicking

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 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 An unmanned aerial vehicle visible light remote sensing image dataset of four forest dynamic plots in subtropical China

2021 ◽  
Vol 29 (9) ◽  
pp. 1181-1185
Author(s):  
Zhaochen Zhang ◽  
Jianbo Hu ◽  
Qingsong Yang ◽  
Juyu Lian ◽  
Buhang Li ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Visible Light ◽  
Unmanned Aerial Vehicle ◽  
Remote Sensing Image ◽  
Subtropical China ◽  
Forest Dynamic ◽  
Image Dataset ◽  
Aerial Vehicle
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