The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
Copyrights notice
The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
Dalam beberapa tahun kebelakangan ini, imej yang ditangkap oleh AVHRR (Advanced Very High Resolution Radiometer) pada siri satelit NOAA (National Oceanic and Atmospheric Administration) telah digunakan secara meluas untuk pemantauan alam sekitar dan penutup tanah. Untuk menggunakan imej NOAA, ia perlu diubah dengan tepat daripada sistem koordinat imej kepada sistem koordinat peta. Kertas kerja ini mencadangkan kaedah pembetulan geometri yang membetulkan ralat yang disebabkan oleh transformasi ini. Dalam kaedah ini, ralat dalam imej NOAA diperbetulkan dalam sistem koordinat imej sebelum berubah menjadi sistem koordinat peta. Pertama, nilai ketinggian, yang dibaca daripada pangkalan data GTOPO30, disahkan untuk membahagikan data kepada blok rata dan kasar. Seterusnya, untuk meningkatkan bilangan GCP (Titik Kawalan Tanah), selain GCP dalam pangkalan data, lebih banyak GCP dijana berdasarkan ciri garis pantai. Selepas menggunakan imej rujukan untuk membetulkan garisan dan piksel hingar yang hilang di bahagian atas dan bawah imej, ralat ketinggian templat GCP diperbetulkan dan pemadanan templat GCP digunakan untuk mencari ralat baki bagi blok yang sepadan dengan templat GCP. Berdasarkan bongkah ini, ralat baki bongkah rata dan kasar lain dikira masing-masing mengikut transformasi affine dan Radial Basis Function. Mengikut ralat baki, semua piksel dalam imej dialihkan ke kedudukan yang betul. Akhirnya, data diubah daripada imej ke peta dengan interpolasi bilinear. Dengan kaedah yang dicadangkan, nilai purata ralat selepas pembetulan adalah lebih kecil daripada 0.2 piksel pada kedua-dua arah latitud dan longitud. Keputusan ini membuktikan bahawa kaedah yang dicadangkan adalah kaedah pembetulan geometri yang sangat tepat.
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Salinan
An Ngoc VAN, Mitsuru NAKAZAWA, Yoshimitsu AOKI, "Highly Accurate Geometric Correction for NOAA AVHRR Data Considering Elevation Effect and Coastline Features" in IEICE TRANSACTIONS on Communications,
vol. E91-B, no. 9, pp. 2956-2963, September 2008, doi: 10.1093/ietcom/e91-b.9.2956.
Abstract: In recent years, the images captured by AVHRR (Advanced Very High Resolution Radiometer) on the NOAA (National Oceanic and Atmospheric Administration) series of satellites have been used very widely for environment and land cover monitoring. In order to use NOAA images, they need to be accurately transformed from the image coordinate system into map coordinate system. This paper proposes a geometric correction method that corrects the errors caused by this transformation. In this method, the errors in NOAA image are corrected in the image coordinate system before transforming into the map coordinate system. First, the elevation values, which are read from GTOPO30 database, are verified to divide data into flat and rough blocks. Next, in order to increase the number of GCPs (Ground Control Points), besides the GCPs in the database, more GCPs are generated based on the feature of the coastline. After using reference images to correct the missing lines and noise pixels in the top and bottom parts of the image, the elevation errors of the GCP templates are corrected and GCP template matching is applied to find the residual errors for the blocks that match GCP templates. Based on these blocks, the residual errors of other flat and rough blocks are calculated by affine and Radial Basis Function transform respectively. According to the residual errors, all pixels in the image are moved to their correct positions. Finally, data is transformed from image into map by bilinear interpolation. With the proposed method, the average values of the error after correction are smaller than 0.2 pixels on both latitude and longitude directions. This result proved that the proposed method is a highly accurate geometric correction method.
URL: https://global.ieice.org/en_transactions/communications/10.1093/ietcom/e91-b.9.2956/_p
Salinan
@ARTICLE{e91-b_9_2956,
author={An Ngoc VAN, Mitsuru NAKAZAWA, Yoshimitsu AOKI, },
journal={IEICE TRANSACTIONS on Communications},
title={Highly Accurate Geometric Correction for NOAA AVHRR Data Considering Elevation Effect and Coastline Features},
year={2008},
volume={E91-B},
number={9},
pages={2956-2963},
abstract={In recent years, the images captured by AVHRR (Advanced Very High Resolution Radiometer) on the NOAA (National Oceanic and Atmospheric Administration) series of satellites have been used very widely for environment and land cover monitoring. In order to use NOAA images, they need to be accurately transformed from the image coordinate system into map coordinate system. This paper proposes a geometric correction method that corrects the errors caused by this transformation. In this method, the errors in NOAA image are corrected in the image coordinate system before transforming into the map coordinate system. First, the elevation values, which are read from GTOPO30 database, are verified to divide data into flat and rough blocks. Next, in order to increase the number of GCPs (Ground Control Points), besides the GCPs in the database, more GCPs are generated based on the feature of the coastline. After using reference images to correct the missing lines and noise pixels in the top and bottom parts of the image, the elevation errors of the GCP templates are corrected and GCP template matching is applied to find the residual errors for the blocks that match GCP templates. Based on these blocks, the residual errors of other flat and rough blocks are calculated by affine and Radial Basis Function transform respectively. According to the residual errors, all pixels in the image are moved to their correct positions. Finally, data is transformed from image into map by bilinear interpolation. With the proposed method, the average values of the error after correction are smaller than 0.2 pixels on both latitude and longitude directions. This result proved that the proposed method is a highly accurate geometric correction method.},
keywords={},
doi={10.1093/ietcom/e91-b.9.2956},
ISSN={1745-1345},
month={September},}
Salinan
TY - JOUR
TI - Highly Accurate Geometric Correction for NOAA AVHRR Data Considering Elevation Effect and Coastline Features
T2 - IEICE TRANSACTIONS on Communications
SP - 2956
EP - 2963
AU - An Ngoc VAN
AU - Mitsuru NAKAZAWA
AU - Yoshimitsu AOKI
PY - 2008
DO - 10.1093/ietcom/e91-b.9.2956
JO - IEICE TRANSACTIONS on Communications
SN - 1745-1345
VL - E91-B
IS - 9
JA - IEICE TRANSACTIONS on Communications
Y1 - September 2008
AB - In recent years, the images captured by AVHRR (Advanced Very High Resolution Radiometer) on the NOAA (National Oceanic and Atmospheric Administration) series of satellites have been used very widely for environment and land cover monitoring. In order to use NOAA images, they need to be accurately transformed from the image coordinate system into map coordinate system. This paper proposes a geometric correction method that corrects the errors caused by this transformation. In this method, the errors in NOAA image are corrected in the image coordinate system before transforming into the map coordinate system. First, the elevation values, which are read from GTOPO30 database, are verified to divide data into flat and rough blocks. Next, in order to increase the number of GCPs (Ground Control Points), besides the GCPs in the database, more GCPs are generated based on the feature of the coastline. After using reference images to correct the missing lines and noise pixels in the top and bottom parts of the image, the elevation errors of the GCP templates are corrected and GCP template matching is applied to find the residual errors for the blocks that match GCP templates. Based on these blocks, the residual errors of other flat and rough blocks are calculated by affine and Radial Basis Function transform respectively. According to the residual errors, all pixels in the image are moved to their correct positions. Finally, data is transformed from image into map by bilinear interpolation. With the proposed method, the average values of the error after correction are smaller than 0.2 pixels on both latitude and longitude directions. This result proved that the proposed method is a highly accurate geometric correction method.
ER -