研究目的
To develop a new framework to sharpen Sentinel-2A imagery with various spatial resolutions of 20 and 60 m to 10 m using higher spatial resolution bands at 10 m and enhance the spectral and spatial quality of sharpened Sentinel-2A imagery compared to existing sharpening algorithms.
研究成果
The proposed sharpening method improves spatial and spectral properties compared to existing methods. CS-based algorithms with the selected band scheme yield higher spatial quality, while MRA-based algorithms with the synthesized band scheme yield higher spectral quality. Future work will extend to other satellite images and sensors.
研究不足
The study is limited to Sentinel-2A imagery and specific algorithms (CS and MRA based); it does not address other satellite images or heterogeneous sensors. The sharpening results show differing tendencies between CS and MRA methods, indicating a trade-off between spatial and spectral quality.
1:Experimental Design and Method Selection:
The study proposes a two-step sharpening algorithm based on modified selected and synthesized band schemes using layer-stacked bands. It involves component substitution (CS) and multiresolution analysis (MRA) based pan-sharpening algorithms such as GSA, GIHS, GS2, and MTF-GLP.
2:Sample Selection and Data Sources:
Two study areas (Site 1 and Site 2) covered by 1800x1800 pixels in bands with 10 m spatial resolution from Sentinel-2A satellite imagery taken on 6 August 2016 and 16 October
3:List of Experimental Equipment and Materials:
20 Sentinel-2A satellite imagery (Level-1C products), MTF filter for image degradation, and software for implementing algorithms.
4:Experimental Procedures and Operational Workflow:
First, sharpen MS60 bands (60 m) to 10 m using MS10 and MS20 bands; second, sharpen MS20 bands (20 m) to 10 m using MS10 and sharpened MS
5:Band-layer stacking is used to improve regression analysis. Data Analysis Methods:
Quantitative evaluation using ERGAS, SAM, UIQI, and sCC indices; qualitative evaluation through visual inspection.
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