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An efficient mosaic algorithm considering seasonal variation: application to KOMPSAT-2 satellite images
Jaewon Choi1, Hyung-Sup Jung2, Sang-Ho Yun3
1The Department of Geoinformatics, The University of Seoul, Seoul 130-743, Korea. jwchoi74@uos.ac.kr.
Sensors (Basel, Switzerland)
|March 12, 2015
Summary
This study introduces an efficient algorithm for creating high-quality mosaic images from satellite data, even with seasonal changes. The method ensures seamless integration of high-resolution optical images for diverse applications.
Area of Science:
- Earth Observation
- Remote Sensing
- Photogrammetry
Background:
- Growing aerospace industry drives demand for high-resolution (HR) optical satellite imagery.
- Generating high-quality mosaic images from HR optical data is a significant challenge, especially with seasonal variations.
Purpose of the Study:
- To propose an efficient mosaic algorithm for HR optical images affected by seasonal changes.
- To validate the algorithm's effectiveness using Kompsat-2 imagery with seasonal variations.
Main Methods:
- Seamline extraction using gradient magnitude and seam images.
- Histogram matching for radiometric consistency.
- Image feathering for smooth transitions.
Main Results:
- The proposed algorithm effectively mosaics adjacent Kompsat-2 images despite severe seasonal changes.
- Demonstrated successful mosaicking of HR optical images with significant seasonal differences.
Conclusions:
- The developed mosaic algorithm is efficient and robust for HR optical images.
- The method is applicable to various HR optical satellite data, including GeoEye, IKONOS, and WorldView.
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