A non-parameterized method for co-registration of panchromatic and multispectral images

Precise co-registration of panchromatic and multispectral images can be challenging due to the imperfect alignment of different sensors from the same platform or the involvement of different platforms. However, conventional methods heavily depending on the quality of feature matching and parameteriz...

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Main Author: J. Peng
Format: Article
Language:English
Published: Copernicus Publications 2014-09-01
Series:The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Online Access:http://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XL-7/141/2014/isprsarchives-XL-7-141-2014.pdf
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spelling doaj-58f0e21d388f48e8a6727ed477205cff2020-11-25T00:43:13ZengCopernicus PublicationsThe International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences1682-17502194-90342014-09-01XL-714114610.5194/isprsarchives-XL-7-141-2014A non-parameterized method for co-registration of panchromatic and multispectral imagesJ. Peng0School of Remote Sensing and Information Engineering, Wuhan University, Wuhan, 430079, ChinaPrecise co-registration of panchromatic and multispectral images can be challenging due to the imperfect alignment of different sensors from the same platform or the involvement of different platforms. However, conventional methods heavily depending on the quality of feature matching and parameterized model fitting fail to yield an accurate result if the relative deformation between images is large. We propose a non-parameterized method that is free of such problems. A basic functional model is established with the consideration of equal radiance and smooth regularization. The local radiance deformation and the self-tuning weighting are then introduced to make the model more suitable for the specific requirement of co-registration. The model is finally solved with a twostage coarse-to-fine optimization approach. Our experiment on ZY-3 (China) images demonstrates its superiority over conventional methods, especially when large deformation due to terrain relief and sensor mis-alignment exists.http://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XL-7/141/2014/isprsarchives-XL-7-141-2014.pdf
collection DOAJ
language English
format Article
sources DOAJ
author J. Peng
spellingShingle J. Peng
A non-parameterized method for co-registration of panchromatic and multispectral images
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
author_facet J. Peng
author_sort J. Peng
title A non-parameterized method for co-registration of panchromatic and multispectral images
title_short A non-parameterized method for co-registration of panchromatic and multispectral images
title_full A non-parameterized method for co-registration of panchromatic and multispectral images
title_fullStr A non-parameterized method for co-registration of panchromatic and multispectral images
title_full_unstemmed A non-parameterized method for co-registration of panchromatic and multispectral images
title_sort non-parameterized method for co-registration of panchromatic and multispectral images
publisher Copernicus Publications
series The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
issn 1682-1750
2194-9034
publishDate 2014-09-01
description Precise co-registration of panchromatic and multispectral images can be challenging due to the imperfect alignment of different sensors from the same platform or the involvement of different platforms. However, conventional methods heavily depending on the quality of feature matching and parameterized model fitting fail to yield an accurate result if the relative deformation between images is large. We propose a non-parameterized method that is free of such problems. A basic functional model is established with the consideration of equal radiance and smooth regularization. The local radiance deformation and the self-tuning weighting are then introduced to make the model more suitable for the specific requirement of co-registration. The model is finally solved with a twostage coarse-to-fine optimization approach. Our experiment on ZY-3 (China) images demonstrates its superiority over conventional methods, especially when large deformation due to terrain relief and sensor mis-alignment exists.
url http://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XL-7/141/2014/isprsarchives-XL-7-141-2014.pdf
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