A JITTER DETECTION METHOD BASED ON THE INTEGRATION IMAGING MODEL
Satellite jitter is a random error source which leads to image degradation. This paper proposes a method to detect the time-variant jitter using multispectral images. In the method, multispectral images are adopted for their large overlap to obtain the parallax map. The imaging process is analyzed i...
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2020-08-01
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doaj-6dc47b26ec5a47508a4be305d74a472d2020-11-25T02:50:12ZengCopernicus PublicationsISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences2194-90422194-90502020-08-01V-3-202070971510.5194/isprs-annals-V-3-2020-709-2020A JITTER DETECTION METHOD BASED ON THE INTEGRATION IMAGING MODELG. Ye0J. Pan1Y. Zhu2S. Jin3State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, ChinaState Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, ChinaState Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, ChinaState Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, ChinaSatellite jitter is a random error source which leads to image degradation. This paper proposes a method to detect the time-variant jitter using multispectral images. In the method, multispectral images are adopted for their large overlap to obtain the parallax map. The imaging process is analyzed in details, and an integration imaging model is constructed, which takes fully into account the time-variant jitter property and builds the relationship between object space with image space. Besides, multispectral images of ZY-3 satellite were used for experiments, and results show that the presented method obtains the jitter curve with the error of amplitude, frequency and phase not more than 0.0591 px, 0.0006 Hz and 0.007 rad, respectively. Results demonstrate the performance of the presented method in jitter detection.https://www.isprs-ann-photogramm-remote-sens-spatial-inf-sci.net/V-3-2020/709/2020/isprs-annals-V-3-2020-709-2020.pdf |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
G. Ye J. Pan Y. Zhu S. Jin |
spellingShingle |
G. Ye J. Pan Y. Zhu S. Jin A JITTER DETECTION METHOD BASED ON THE INTEGRATION IMAGING MODEL ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
author_facet |
G. Ye J. Pan Y. Zhu S. Jin |
author_sort |
G. Ye |
title |
A JITTER DETECTION METHOD BASED ON THE INTEGRATION IMAGING MODEL |
title_short |
A JITTER DETECTION METHOD BASED ON THE INTEGRATION IMAGING MODEL |
title_full |
A JITTER DETECTION METHOD BASED ON THE INTEGRATION IMAGING MODEL |
title_fullStr |
A JITTER DETECTION METHOD BASED ON THE INTEGRATION IMAGING MODEL |
title_full_unstemmed |
A JITTER DETECTION METHOD BASED ON THE INTEGRATION IMAGING MODEL |
title_sort |
jitter detection method based on the integration imaging model |
publisher |
Copernicus Publications |
series |
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
issn |
2194-9042 2194-9050 |
publishDate |
2020-08-01 |
description |
Satellite jitter is a random error source which leads to image degradation. This paper proposes a method to detect the time-variant jitter using multispectral images. In the method, multispectral images are adopted for their large overlap to obtain the parallax map. The imaging process is analyzed in details, and an integration imaging model is constructed, which takes fully into account the time-variant jitter property and builds the relationship between object space with image space. Besides, multispectral images of ZY-3 satellite were used for experiments, and results show that the presented method obtains the jitter curve with the error of amplitude, frequency and phase not more than 0.0591 px, 0.0006 Hz and 0.007 rad, respectively. Results demonstrate the performance of the presented method in jitter detection. |
url |
https://www.isprs-ann-photogramm-remote-sens-spatial-inf-sci.net/V-3-2020/709/2020/isprs-annals-V-3-2020-709-2020.pdf |
work_keys_str_mv |
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