Results 11 to 20 of about 3,858,794 (311)
An Uncertainty Descriptor for Quantitative Measurement of the Uncertainty of Remote Sensing Images
Remote Sensing, 2019 Reliable image classification results are crucial for the application of remote sensing images, but the reliability of image classification has received less attention. In particular, the inherent uncertainty of remote sensing images has been disregarded.
Qi Zhang, Penglin Zhang
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Stripe Noise Detection of High-Resolution Remote Sensing Images Using Deep Learning Method
Remote Sensing, 2022 Stripe noise is considered one of the largest issues in space-borne remote sensing. The features of stripe noise in high-resolution remote sensing images are varied in different spatiotemporal conditions, leading to limited detection capability.
Binbo Li +6 more
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Novel folded-PCA for improved feature extraction and data reduction with hyperspectral imaging and SAR in remote sensing [PDF]
, 2014 As a widely used approach for feature extraction and data reduction, Principal Components Analysis (PCA) suffers from high computational cost, large memory requirement and low efficacy in dealing with large dimensional datasets such as Hyperspectral ...
Han, Junwei +6 more
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PRIMITIVE-BASED BUILDING RECONSTRUCTION BY INTEGRATION OF LIDAR DATA AND OPTICAL IMAGERY [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2012 Airborne LiDAR data and optical imagery are two datasets used for 3D building reconstruction. In this paper, the complementarities of these two datasets are utilized to perform a primitive-based 3D building reconstruction.
W. Zhang +3 more
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IEEE Access, 2023 Since hyperspectral remote sensing images are three-dimensional data cubes with spatial and spectral information, with many wavebands and high inter-band correlation, the number of training samples required for classification is greatly increased.
Chaozhu Zhang +3 more
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IET Image Processing, 2022 Although hyperspectral data, especially spaceborne images, are rich in spectral information, their spatial resolution is usually low due to the limitation of sensor design and other factors.
Haoyang Yu +5 more
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Object-Based Land Cover Classification for ALOS Image Combining TM Spectral [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2013 Land cover classification for high spatial resolution remote sensing images becomes a challenging work. The high spatial resolution remote sensing images have more spatial information.
G. Wang, J. Liu, G. He
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A Novel Deep Nearest Neighbor Neural Network for Few-Shot Remote Sensing Image Scene Classification
Remote Sensing, 2023 Remote sensing image scene classification has become more and more popular in recent years. As we all know, it is very difficult and time-consuming to obtain a large number of manually labeled remote sensing images.
Yanqiao Chen +4 more
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Atmospheric Light Estimation Based Remote Sensing Image Dehazing
Remote Sensing, 2021 Remote sensing images are widely used in object detection and tracking, military security, and other computer vision tasks. However, remote sensing images are often degraded by suspended aerosol in the air, especially under poor weather conditions, such ...
Zhiqin Zhu +7 more
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Multiscale Classification of Remote Sensing Images [PDF]
IEEE Transactions on Geoscience and Remote Sensing, 2012 A huge effort has been applied in image classification to create high-quality thematic maps and to establish precise inventories about land cover use. The peculiarities of remote sensing images (RSIs) combined with the traditional image classification challenges made RSI classification a hard task.
Jefersson Alex dos Santos +4 more
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