Remote Sensing Single-Image Superresolution Based on a Deep Compendium Model

J. M. Haut; M. E. Paoletti; R. Fernandez-Beltran; J. Plaza; A. Plaza; Jun Li

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Remote Sensing Single-Image Superresolution Based on a Deep Compendium Model

机译：基于深度纲要模型的遥感单图像超分辨率

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This letter introduces a novel remote sensing single-image superresolution (SR) architecture based on a deep efficient compendium model. The current deep learning-based SR trend stands for using deeper networks to improve the performance. However, this pr

机译：这封信介绍了一种基于深度有效纲要模型的新颖的遥感单图像超分辨率（SR）体系结构。当前基于深度学习的SR趋势代表使用更深的网络来提高性能。但是，这个公关

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来源
《IEEE Geoscience and Remote Sensing Letters》 |2019年第9期|1432-1436|共5页
作者
J. M. Haut; M. E. Paoletti; R. Fernandez-Beltran; J. Plaza; A. Plaza; Jun Li;
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作者单位

Department of Technology of Computers and Communications Hyperspectral Computing Laboratory Escuela Politécnica University of Extremadura Cáceres Spain;

Department of Technology of Computers and Communications Hyperspectral Computing Laboratory Escu;

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原文格式 PDF
正文语种 eng
中图分类
关键词
Remote sensing; Spatial resolution; Kernel; Visualization; Training; Signal resolution;

机译：遥感;空间分辨率;核心;可视化;训练;信号分辨率;

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1. Superresolution Approach of Remote Sensing Images based on Deep Convolutional Neural Network [J] . Jitao Zhang, Aili Wang, Na An, International Journal of Performability Engineering . 2018,第3期

机译：基于深卷积神经网络的遥感图像超级化方法
2. Superresolution Mapping of Remotely Sensed Image Based on Hopfield Neural Network With Anisotropic Spatial Dependence Model [J] . IEEE Geoscience and Remote Sensing Letters . 2014,第7期

机译：基于各向异性空间依赖模型的Hopfield神经网络的遥感图像超分辨率映射
3. A New Deep Generative Network for Unsupervised Remote Sensing Single-Image Super-Resolution [J] . Juan Mario Haut, Ruben Fernandez-Beltran, Mercedes E. Paoletti, IEEE Transactions on Geoscience and Remote Sensing. . 2018,第11期

机译：一种新型的深度生成网络，用于无监督遥感单图像超分辨率
4. Single-Image Super-Resolution for Remote Sensing Data Using Deep Residual-Learning Neural Network [C] . Ningbo Huang, Yong Yang, Junjie Liu, International conference on neural information processing . 2017

机译：使用深度残差学习神经网络的遥感图像单图像超分辨率
5. Validation of remotely-sensed soil moisture observations for bare soil at 1.4 GHz: A quantitative approach through radiative transfer models to characterize abrupt transitions caused by a ponding event in an agricultural field, modifications to the radiative transfer models, and a mobile ground-based system [D] . Erbas, Cihan 2009

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7. Remote Sensing Single-Image Superresolution Based on a Deep Compendium Model [O] . J. M. Haut, M. E. Paoletti, R. Fernandez-Beltran, 2019

机译：基于深度概要模型的遥感单图像超级度
8. Environmental application of remote sensing methods to coastal zone land use and marine resource management. The potential of remote sensing as a data base for state agencies - The Virginia model [R] . Goodell, H. G., Reed, W. 1971

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Remote Sensing Single-Image Superresolution Based on a Deep Compendium Model

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