Seamless Mosaicking of UAV-Based Push-Broom Hyperspectral Images for Environment Monitoring

This paper proposes a systematic image mosaicking methodology to produce hyperspectral image for environment monitoring using an emerging UAV-based push-broom hyperspectral imager. The suitability of alternative methods in each step is assessed by experiments of an urban scape, a river course and a...

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Autores principales:	Lina Yi, Jing M. Chen, Guifeng Zhang, Xiao Xu, Xing Ming, Wenji Guo
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	geometric rectification image registration image fusion spectral fidelity Science Q
Acceso en línea:	https://doaj.org/article/2f4438176c8649529e512da6cafa83a6
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spelling	oai:doaj.org-article:2f4438176c8649529e512da6cafa83a62021-11-25T18:55:46ZSeamless Mosaicking of UAV-Based Push-Broom Hyperspectral Images for Environment Monitoring10.3390/rs132247202072-4292https://doaj.org/article/2f4438176c8649529e512da6cafa83a62021-11-01T00:00:00Zhttps://www.mdpi.com/2072-4292/13/22/4720https://doaj.org/toc/2072-4292This paper proposes a systematic image mosaicking methodology to produce hyperspectral image for environment monitoring using an emerging UAV-based push-broom hyperspectral imager. The suitability of alternative methods in each step is assessed by experiments of an urban scape, a river course and a forest study area. First, the hyperspectral image strips were acquired by sequentially stitching the UAV images acquired by push-broom scanning along each flight line. Next, direct geo-referencing was applied to each image strip to get initial geo-rectified result. Then, with ground control points, the curved surface spline function was used to transform the initial geo-rectified image strips to improve their geometrical accuracy. To further remove the displacement between pairs of image strips, an improved phase correlation (IPC) and a SIFT and RANSAC-based method (SR) were used in image registration. Finally, the weighted average and the best stitching image fusion method were used to remove the spectral differences between image strips and get the seamless mosaic. Experiment results showed that as the GCPs‘ number increases, the mosaicked image‘s geometrical accuracy increases. In image registration, there exists obvious edge information that can be accurately extracted from the urban scape and river course area; comparative results can be achieved by the IPC method with less time cost. However, for the ground objects with complex texture like forest, the edges extracted from the image is prone to be inaccurate and result in the failure of the IPC method, and only the SR method can get a good result. In image fusion, the best stitching fusion method can get seamless results for all three study areas. Whereas, the weighted average fusion method was only useful in eliminating the stitching line for the river course and forest areas but failed for the urban scape area due to the spectral heterogeneity of different ground objects. For different environment monitoring applications, the proposed methodology provides a practical solution to seamlessly mosaic UAV-based push-broom hyperspectral images with high geometrical accuracy and spectral fidelity.Lina YiJing M. ChenGuifeng ZhangXiao XuXing MingWenji GuoMDPI AGarticlegeometric rectificationimage registrationimage fusionspectral fidelityScienceQENRemote Sensing, Vol 13, Iss 4720, p 4720 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	geometric rectification image registration image fusion spectral fidelity Science Q
spellingShingle	geometric rectification image registration image fusion spectral fidelity Science Q Lina Yi Jing M. Chen Guifeng Zhang Xiao Xu Xing Ming Wenji Guo Seamless Mosaicking of UAV-Based Push-Broom Hyperspectral Images for Environment Monitoring
description	This paper proposes a systematic image mosaicking methodology to produce hyperspectral image for environment monitoring using an emerging UAV-based push-broom hyperspectral imager. The suitability of alternative methods in each step is assessed by experiments of an urban scape, a river course and a forest study area. First, the hyperspectral image strips were acquired by sequentially stitching the UAV images acquired by push-broom scanning along each flight line. Next, direct geo-referencing was applied to each image strip to get initial geo-rectified result. Then, with ground control points, the curved surface spline function was used to transform the initial geo-rectified image strips to improve their geometrical accuracy. To further remove the displacement between pairs of image strips, an improved phase correlation (IPC) and a SIFT and RANSAC-based method (SR) were used in image registration. Finally, the weighted average and the best stitching image fusion method were used to remove the spectral differences between image strips and get the seamless mosaic. Experiment results showed that as the GCPs‘ number increases, the mosaicked image‘s geometrical accuracy increases. In image registration, there exists obvious edge information that can be accurately extracted from the urban scape and river course area; comparative results can be achieved by the IPC method with less time cost. However, for the ground objects with complex texture like forest, the edges extracted from the image is prone to be inaccurate and result in the failure of the IPC method, and only the SR method can get a good result. In image fusion, the best stitching fusion method can get seamless results for all three study areas. Whereas, the weighted average fusion method was only useful in eliminating the stitching line for the river course and forest areas but failed for the urban scape area due to the spectral heterogeneity of different ground objects. For different environment monitoring applications, the proposed methodology provides a practical solution to seamlessly mosaic UAV-based push-broom hyperspectral images with high geometrical accuracy and spectral fidelity.
format	article
author	Lina Yi Jing M. Chen Guifeng Zhang Xiao Xu Xing Ming Wenji Guo
author_facet	Lina Yi Jing M. Chen Guifeng Zhang Xiao Xu Xing Ming Wenji Guo
author_sort	Lina Yi
title	Seamless Mosaicking of UAV-Based Push-Broom Hyperspectral Images for Environment Monitoring
title_short	Seamless Mosaicking of UAV-Based Push-Broom Hyperspectral Images for Environment Monitoring
title_full	Seamless Mosaicking of UAV-Based Push-Broom Hyperspectral Images for Environment Monitoring
title_fullStr	Seamless Mosaicking of UAV-Based Push-Broom Hyperspectral Images for Environment Monitoring
title_full_unstemmed	Seamless Mosaicking of UAV-Based Push-Broom Hyperspectral Images for Environment Monitoring
title_sort	seamless mosaicking of uav-based push-broom hyperspectral images for environment monitoring
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/2f4438176c8649529e512da6cafa83a6
work_keys_str_mv	AT linayi seamlessmosaickingofuavbasedpushbroomhyperspectralimagesforenvironmentmonitoring AT jingmchen seamlessmosaickingofuavbasedpushbroomhyperspectralimagesforenvironmentmonitoring AT guifengzhang seamlessmosaickingofuavbasedpushbroomhyperspectralimagesforenvironmentmonitoring AT xiaoxu seamlessmosaickingofuavbasedpushbroomhyperspectralimagesforenvironmentmonitoring AT xingming seamlessmosaickingofuavbasedpushbroomhyperspectralimagesforenvironmentmonitoring AT wenjiguo seamlessmosaickingofuavbasedpushbroomhyperspectralimagesforenvironmentmonitoring
_version_	1718410513408327680

Seamless Mosaicking of UAV-Based Push-Broom Hyperspectral Images for Environment Monitoring

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