Mosaicking and Correction Method of Gaofen-3 ScanSAR Images in Coastal Areas with Subswath Overlap Range Constraints

The ScanSAR mode image obtained by the Gaofen-3 (GF-3) satellite has an imaging width of up to 130–500 km, which is of great significance in monitoring oceanography, meteorology, water conservancy, and transportation. To address the issues of subswath misalignment and the inability to correct in the...

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Main Authors: Jiajun Wang, Guowang Jin, Xin Xiong, Jiahao Li, Hao Ye, He Yang
Format: Article
Language:English
Published: MDPI AG 2024-12-01
Series:Journal of Marine Science and Engineering
Subjects:
Online Access:https://www.mdpi.com/2077-1312/12/12/2277
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author Jiajun Wang
Guowang Jin
Xin Xiong
Jiahao Li
Hao Ye
He Yang
author_facet Jiajun Wang
Guowang Jin
Xin Xiong
Jiahao Li
Hao Ye
He Yang
author_sort Jiajun Wang
collection DOAJ
description The ScanSAR mode image obtained by the Gaofen-3 (GF-3) satellite has an imaging width of up to 130–500 km, which is of great significance in monitoring oceanography, meteorology, water conservancy, and transportation. To address the issues of subswath misalignment and the inability to correct in the processing of GF-3 ScanSAR images in coastal areas using software such as PIE, ENVI, and SNAP, a method for mosaicking and correcting GF-3 ScanSAR images with subswaths that overlap within specified range constraints is proposed. This method involves correlating the coefficients of each subswath thumbnail image in order to determine the extent of the overlap range. Given that the matching points are constrained to the overlap between subswaths, the normalized cross-correlation (NCC) matching algorithm is utilized to calculate the matching points between subswaths. Subsequently, the random sampling consistency (RANSAC) algorithm is employed to eliminate the mismatching points. Subsequently, the subswaths should be mosaicked together with the stitching translation of subswaths, based on the coordinates of the matching points. The image brightness correction coefficient is calculated based on the average grayscale value of pixels in the overlapping region. This is performed in order to correct the grayscale values of adjacent subswaths and thereby reducing the brightness difference at the junction of subswaths. The entire ScanSAR slant range image is produced. By employing the Range–Doppler model for indirect orthorectification, corrected images with geographic information are generated. The experiment utilized three coastal GF-3 ScanSAR images for mosaicking and correction, and the results were contrasted with those attained through PIE software V7.0 processing. This was conducted to substantiate the efficacy and precision of the methodology for mosaicking and correcting coastal GF-3 ScanSAR images.
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spelling doaj-art-6ca5eb0030174a129afc357cd6b69bde2025-08-20T02:00:46ZengMDPI AGJournal of Marine Science and Engineering2077-13122024-12-011212227710.3390/jmse12122277Mosaicking and Correction Method of Gaofen-3 ScanSAR Images in Coastal Areas with Subswath Overlap Range ConstraintsJiajun Wang0Guowang Jin1Xin Xiong2Jiahao Li3Hao Ye4He Yang5Institute of Geospatial Information, Information Engineering University, Zhengzhou 450001, ChinaInstitute of Geospatial Information, Information Engineering University, Zhengzhou 450001, ChinaInstitute of Geospatial Information, Information Engineering University, Zhengzhou 450001, ChinaInstitute of Geospatial Information, Information Engineering University, Zhengzhou 450001, ChinaInstitute of Geospatial Information, Information Engineering University, Zhengzhou 450001, ChinaTransportation Development Center of Henan Province, Zhengzhou 450016, ChinaThe ScanSAR mode image obtained by the Gaofen-3 (GF-3) satellite has an imaging width of up to 130–500 km, which is of great significance in monitoring oceanography, meteorology, water conservancy, and transportation. To address the issues of subswath misalignment and the inability to correct in the processing of GF-3 ScanSAR images in coastal areas using software such as PIE, ENVI, and SNAP, a method for mosaicking and correcting GF-3 ScanSAR images with subswaths that overlap within specified range constraints is proposed. This method involves correlating the coefficients of each subswath thumbnail image in order to determine the extent of the overlap range. Given that the matching points are constrained to the overlap between subswaths, the normalized cross-correlation (NCC) matching algorithm is utilized to calculate the matching points between subswaths. Subsequently, the random sampling consistency (RANSAC) algorithm is employed to eliminate the mismatching points. Subsequently, the subswaths should be mosaicked together with the stitching translation of subswaths, based on the coordinates of the matching points. The image brightness correction coefficient is calculated based on the average grayscale value of pixels in the overlapping region. This is performed in order to correct the grayscale values of adjacent subswaths and thereby reducing the brightness difference at the junction of subswaths. The entire ScanSAR slant range image is produced. By employing the Range–Doppler model for indirect orthorectification, corrected images with geographic information are generated. The experiment utilized three coastal GF-3 ScanSAR images for mosaicking and correction, and the results were contrasted with those attained through PIE software V7.0 processing. This was conducted to substantiate the efficacy and precision of the methodology for mosaicking and correcting coastal GF-3 ScanSAR images.https://www.mdpi.com/2077-1312/12/12/2277scanning synthetic aperture radar (ScanSAR)image mosaicnormalized cross-correlation coefficientRANSACGaofen-3
spellingShingle Jiajun Wang
Guowang Jin
Xin Xiong
Jiahao Li
Hao Ye
He Yang
Mosaicking and Correction Method of Gaofen-3 ScanSAR Images in Coastal Areas with Subswath Overlap Range Constraints
Journal of Marine Science and Engineering
scanning synthetic aperture radar (ScanSAR)
image mosaic
normalized cross-correlation coefficient
RANSAC
Gaofen-3
title Mosaicking and Correction Method of Gaofen-3 ScanSAR Images in Coastal Areas with Subswath Overlap Range Constraints
title_full Mosaicking and Correction Method of Gaofen-3 ScanSAR Images in Coastal Areas with Subswath Overlap Range Constraints
title_fullStr Mosaicking and Correction Method of Gaofen-3 ScanSAR Images in Coastal Areas with Subswath Overlap Range Constraints
title_full_unstemmed Mosaicking and Correction Method of Gaofen-3 ScanSAR Images in Coastal Areas with Subswath Overlap Range Constraints
title_short Mosaicking and Correction Method of Gaofen-3 ScanSAR Images in Coastal Areas with Subswath Overlap Range Constraints
title_sort mosaicking and correction method of gaofen 3 scansar images in coastal areas with subswath overlap range constraints
topic scanning synthetic aperture radar (ScanSAR)
image mosaic
normalized cross-correlation coefficient
RANSAC
Gaofen-3
url https://www.mdpi.com/2077-1312/12/12/2277
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