PANSHARPENING ON THE NARROW VNIR AND SWIR SPECTRAL BANDS OF SENTINEL-2

10 citations as recorded by crossref.

1. Sharpening the VNIR and SWIR Bands of Sentinel-2A Imagery through Modified Selected and Synthesized Band Schemes H. Park et al. https://doi.org/10.3390/rs9101080
2. Sentinel-2 Sharpening via Parallel Residual Network J. Wu et al. https://doi.org/10.3390/rs12020279
3. Adaptive hybrid pansharpening: a novel approach for combining two methods to achieve superior pansharpening performance V. Yilmaz https://doi.org/10.1080/01431161.2023.2234095
4. Monitoring of granite quarries using deep learning and UAV photogrammetry in Bengaluru, India O. Himmy et al. https://doi.org/10.1371/journal.pone.0334493
5. Sharpening of Worldview-3 Satellite Images by Generating Optimal High-Spatial-Resolution Images H. Park et al. https://doi.org/10.3390/app10207313
6. Single-Image Super-Resolution of Sentinel-2 Low Resolution Bands with Residual Dense Convolutional Neural Networks L. Salgueiro et al. https://doi.org/10.3390/rs13245007
7. A Comprehensive Benchmarking Framework for Sentinel-2 Sharpening: Methods, Dataset, and Evaluation Metrics M. Ciotola et al. https://doi.org/10.3390/rs17121983
8. Improving PRISMA hyperspectral spatial resolution and geolocation by using Sentinel-2: development and test of an operational procedure in urban and rural areas G. De Luca et al. https://doi.org/10.1016/j.isprsjprs.2024.07.003
9. Urban land cover mapping with Sentinel-2: a spectro-spatio-temporal analysis F. Xu et al. https://doi.org/10.1007/s44212-022-00008-y
10. Assessment of the Capability of Sentinel-2 Imagery for Iron-Bearing Minerals Mapping: A Case Study in the Cuprite Area, Nevada W. Ge et al. https://doi.org/10.3390/rs12183028