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http://dx.doi.org/10.7780/kjrs.2007.23.4.297

Automated Geometric Correction of Geostationary Weather Satellite Images  

Kim, Hyun-Suk (Department of Geoinformatic Engineering, Inha University)
Lee, Tae-Yoon (Department of Geoinformatic Engineering, Inha University)
Hur, Dong-Seok (Department of Geoinformatic Engineering, Inha University)
Rhee, Soo-Ahm (Department of Geoinformatic Engineering, Inha University)
Kim, Tae-Jung (Department of Geoinformatic Engineering, Inha University)
Publication Information
Korean Journal of Remote Sensing / v.23, no.4, 2007 , pp. 297-309 More about this Journal
Abstract
The first Korean geostationary weather satellite, Communications, Oceanography and Meteorology Satellite (COMS) will be launched in 2008. The ground station for COMS needs to perform geometric correction to improve accuracy of satellite image data and to broadcast geometrically corrected images to users within 30 minutes after image acquisition. For such a requirement, we developed automated and fast geometric correction techniques. For this, we generated control points automatically by matching images against coastline data and by applying a robust estimation called RANSAC. We used GSHHS (Global Self-consistent Hierarchical High-resolution Shoreline) shoreline database to construct 211 landmark chips. We detected clouds within the images and applied matching to cloud-free sub images. When matching visible channels, we selected sub images located in day-time. We tested the algorithm with GOES-9 images. Control points were generated by matching channel 1 and channel 2 images of GOES against the 211 landmark chips. The RANSAC correctly removed outliers from being selected as control points. The accuracy of sensor models established using the automated control points were in the range of $1{\sim}2$ pixels. Geometric correction was performed and the performance was visually inspected by projecting coastline onto the geometrically corrected images. The total processing time for matching, RANSAC and geometric correction was around 4 minutes.
Keywords
cloud detection; sensor model; the resampled images; the automated control point generation; geometric correction; RANSAC; GSHHS; Landmark Chip;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
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