Super-Resolution for Remote Sensing Images via Local–Global Combined Network

By Sen Lei, Zhenwei Shi, Zhengxia Zou. IEEE Geoscience and Remote Sensing Letters, 2017

341 citations recorded by the source corpus.

How researchers see this paper

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TTST: A Top-k Token Selective Transformer for Remote Sensing Image Super-Resolution (2024, methodology): “A. Remote Sensing Image Super-Resolution 1) CNN-Based: Drawing inspiration from SRCNN [32], a crowd of CNN-based SR methods have emerged and made remarkable progress on image SR task [33], [34], [35], [36], [37].”
Edge-Enhanced GAN for Remote Sensing Image Superresolution (2019, neutral): “[42] constructed”
Missing Data Reconstruction in Remote Sensing Image With a Unified Spatial–Temporal–Spectral Deep Convolutional Neural Network (2018, neutral): “cal remote sensing image super-resolution [7], hyperspectral”
Deep Learning for Land Use and Land Cover Classification Based on Hyperspectral and Multispectral Earth Observation Data: A Review (2020, background): “These types of models are getting popular to increase the resolution of remote sensing data too [160,161].”