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of 548
pro vyhledávání: '"Yuan, Qiangqiang"'
Recent progress in remote sensing image (RSI) super-resolution (SR) has exhibited remarkable performance using deep neural networks, e.g., Convolutional Neural Networks and Transformers. However, existing SR methods often suffer from either a limited
Externí odkaz:
http://arxiv.org/abs/2405.04964
Hyperspectral images play a crucial role in precision agriculture, environmental monitoring or ecological analysis. However, due to sensor equipment and the imaging environment, the observed hyperspectral images are often inevitably corrupted by vari
Externí odkaz:
http://arxiv.org/abs/2311.13622
Recently, convolutional networks have achieved remarkable development in remote sensing image Super-Resoltuion (SR) by minimizing the regression objectives, e.g., MSE loss. However, despite achieving impressive performance, these methods often suffer
Externí odkaz:
http://arxiv.org/abs/2310.19288
Autor:
Xiao, Yi, Yuan, Qiangqiang, Jiang, Kui, Jin, Xianyu, He, Jiang, Zhang, Liangpei, Lin, Chia-wen
Publikováno v:
IEEE Transactions on Circuits and Systems for Video Technology, 2023
Optical-flow-based and kernel-based approaches have been extensively explored for temporal compensation in satellite Video Super-Resolution (VSR). However, these techniques are less generalized in large-scale or complex scenarios, especially in satel
Externí odkaz:
http://arxiv.org/abs/2304.04421
Publikováno v:
In Remote Sensing of Environment 1 September 2024 311
Publikováno v:
In Information Fusion September 2024 109
Publikováno v:
In ISPRS Journal of Photogrammetry and Remote Sensing August 2024 214:179-192
Publikováno v:
IEEE Geoscience and Remote Sensing Magazine, vol. 10, no. 2, pp. 231-249, June 2022
In the fields of image restoration and image fusion, model-driven methods and data-driven methods are the two representative frameworks. However, both approaches have their respective advantages and disadvantages. The model-driven methods consider th
Externí odkaz:
http://arxiv.org/abs/2108.06073
The data fusion technology aims to aggregate the characteristics of different data and obtain products with multiple data advantages. To solves the problem of reduced resolution of PolSAR images due to system limitations, we propose a fully polarimet
Externí odkaz:
http://arxiv.org/abs/2107.08355
Publikováno v:
In Information Fusion June 2024 106