Results 31 to 40 of about 49,901 (265)

A Multi-scale features-based cloud detection method for Suomi-NPP VIIRS day and night imagery [PDF]

ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Cloud detection is a necessary step before the application of remote sensing images. However, most methods focus on cloud detection in daytime remote sensing images.
J. Li, C. Hu, Q. Sheng, J. Xu, C. Zhu, W. Zhang   +5 more
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Optical Remote Sensing Image Denoising and Super-Resolution Reconstructing Using Optimized Generative Network in Wavelet Transform Domain

Remote Sensing, 2021
High spatial quality (HQ) optical remote sensing images are very useful for target detection, target recognition and image classification. Due to the influence of imaging equipment accuracy and atmospheric environment, HQ images are difficult to acquire,
Xubin Feng, Wuxia Zhang, Xiuqin Su, Zhengpu Xu   +3 more
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Computational ghost imaging for remote sensing [PDF]

Journal of the Optical Society of America A, 2012
Computational ghost imaging is a structured-illumination active imager coupled with a single-pixel detector that has potential applications in remote sensing. Here we report on an architecture that acquires the two-dimensional spatial Fourier transform of the target object (which can be inverted to obtain a conventional image).
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An interpretable approach for automatic aesthetic assessment of remote sensing images

Frontiers in Computational Neuroscience, 2022
The increase of remote sensing images in recent decades has resulted in their use in non-scientific fields such as environmental protection, education, and art.
Jingru Tong, Guo Zhang, Peijie Kong, Yu Rao, Zhengkai Wei, Hao Cui, Qing Guan   +6 more
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Image Fusion Techniques in Remote Sensing

CoRR, 2014
Remote sensing image fusion is an effective way to use a large volume of data from multisensor images. Most earth satellites such as SPOT, Landsat 7, IKONOS and QuickBird provide both panchromatic (Pan) images at a higher spatial resolution and multispectral (MS) images at a lower spatial resolution and many remote sensing applications require both ...
Reham Gharbia, Ahmad Taher Azar, Ali Hassan El Baz, Aboul Ella Hassanien   +3 more
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RSMT: A Remote Sensing Image-to-Map Translation Model via Adversarial Deep Transfer Learning

Remote Sensing, 2022
Maps can help governments in infrastructure development and emergency rescue operations around the world. Using adversarial learning to generate maps from remote sensing images is an emerging field.
Jieqiong Song, Jun Li, Hao Chen, Jiangjiang Wu   +3 more
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A Review of Image Super-Resolution Approaches Based on Deep Learning and Applications in Remote Sensing

Remote Sensing, 2022
At present, with the advance of satellite image processing technology, remote sensing images are becoming more widely used in real scenes. However, due to the limitations of current remote sensing imaging technology and the influence of the external ...
Xuan Wang, Jinglei Yi, Jian Guo, Yongchao Song, Jun Lyu, Jindong Xu, Weiqing Yan, Jindong Zhao, Qing Cai, Haigen Min   +9 more
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Change Detection in Multitemporal High Spatial Resolution Remote-Sensing Images Based on Saliency Detection and Spatial Intuitionistic Fuzzy C-Means Clustering

Journal of Spectroscopy, 2020
In order to improve the change detection accuracy of multitemporal high spatial resolution remote-sensing (HSRRS) images, a change detection method of multitemporal remote-sensing images based on saliency detection and spatial intuitionistic fuzzy C ...
Liang Huang, Qiuzhi Peng, Xueqin Yu
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Remote Sensing Image Super-Resolution via Multi-Scale Texture Transfer Network

Remote Sensing, 2023
As the degradation factors of remote sensing images become increasingly complex, it becomes challenging to infer the high-frequency details of remote sensing images compared to ordinary digital photographs.
Yu Wang, Zhenfeng Shao, Tao Lu, Xiao Huang, Jiaming Wang, Xitong Chen, Haiyan Huang, Xiaolong Zuo   +7 more
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High-Resolution Remote Sensing Image Information Extraction and Target Recognition Based on Multiple Information Fusion

IEEE Access, 2020
The current research on multiple information fusion of remote sensing images is mainly aimed at remote sensing images of specific satellite sensors, and cannot be extended to other types of data source images.
Yi Liu, Min Chang, Jie Xu
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