Fast and Efficient Method for Large-Scale Aerial Image Stitching
Recent studies on image stitching have been extensively conducted to stitch panoramic or 360° images using a small number of input images. The stitching of aerial images, that are captured by unmanned aerial vehicles (UAVs), has various practical applications. In this paper, we propose a...
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doaj-4b5b65c24c484e3c8ff60720c74046c02021-09-20T23:00:42ZengIEEEIEEE Access2169-35362021-01-01912785212786510.1109/ACCESS.2021.31112039531644Fast and Efficient Method for Large-Scale Aerial Image StitchingNam Thanh Pham0https://orcid.org/0000-0003-2269-910XSihyun Park1Chun-Su Park2https://orcid.org/0000-0003-4250-2597AIPro Inc, Seoul, South KoreaDepartment of Computer Education, Sungkyunkwan University, Seoul, South KoreaAIPro Inc, Seoul, South KoreaRecent studies on image stitching have been extensively conducted to stitch panoramic or 360° images using a small number of input images. The stitching of aerial images, that are captured by unmanned aerial vehicles (UAVs), has various practical applications. In this paper, we propose a fast adaptive stitching algorithm for handling numerous aerial images. First, the proposed method analyzes the relative positions and overlapping regions of the UAV image footprints by exploiting their geotag information. Based on the analysis, an adaptive selection algorithm is proposed to eliminate the densely overlapped images from among all the UAV images. Then, the proposed method sequentially performs fast feature extraction and feature matching. Finally, a local warp method, with a smooth transition for overlapping regions, is introduced to alleviate the blurring artifacts and achieve highly accurate image alignment. The experiments are conducted for various scenarios to generate seamless terrestrial mosaic images of large areas. The proposed method improves the visual quality of the stitched image, by decreasing the estimated reprojection error and the number of observed visual distortions. In addition, the proposed method can substantially reduce the processing time compared with conventional stitching methods.https://ieeexplore.ieee.org/document/9531644/Aerial imageslocal homographystitching |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Nam Thanh Pham Sihyun Park Chun-Su Park |
spellingShingle |
Nam Thanh Pham Sihyun Park Chun-Su Park Fast and Efficient Method for Large-Scale Aerial Image Stitching IEEE Access Aerial images local homography stitching |
author_facet |
Nam Thanh Pham Sihyun Park Chun-Su Park |
author_sort |
Nam Thanh Pham |
title |
Fast and Efficient Method for Large-Scale Aerial Image Stitching |
title_short |
Fast and Efficient Method for Large-Scale Aerial Image Stitching |
title_full |
Fast and Efficient Method for Large-Scale Aerial Image Stitching |
title_fullStr |
Fast and Efficient Method for Large-Scale Aerial Image Stitching |
title_full_unstemmed |
Fast and Efficient Method for Large-Scale Aerial Image Stitching |
title_sort |
fast and efficient method for large-scale aerial image stitching |
publisher |
IEEE |
series |
IEEE Access |
issn |
2169-3536 |
publishDate |
2021-01-01 |
description |
Recent studies on image stitching have been extensively conducted to stitch panoramic or 360° images using a small number of input images. The stitching of aerial images, that are captured by unmanned aerial vehicles (UAVs), has various practical applications. In this paper, we propose a fast adaptive stitching algorithm for handling numerous aerial images. First, the proposed method analyzes the relative positions and overlapping regions of the UAV image footprints by exploiting their geotag information. Based on the analysis, an adaptive selection algorithm is proposed to eliminate the densely overlapped images from among all the UAV images. Then, the proposed method sequentially performs fast feature extraction and feature matching. Finally, a local warp method, with a smooth transition for overlapping regions, is introduced to alleviate the blurring artifacts and achieve highly accurate image alignment. The experiments are conducted for various scenarios to generate seamless terrestrial mosaic images of large areas. The proposed method improves the visual quality of the stitched image, by decreasing the estimated reprojection error and the number of observed visual distortions. In addition, the proposed method can substantially reduce the processing time compared with conventional stitching methods. |
topic |
Aerial images local homography stitching |
url |
https://ieeexplore.ieee.org/document/9531644/ |
work_keys_str_mv |
AT namthanhpham fastandefficientmethodforlargescaleaerialimagestitching AT sihyunpark fastandefficientmethodforlargescaleaerialimagestitching AT chunsupark fastandefficientmethodforlargescaleaerialimagestitching |
_version_ |
1717373886498078720 |