Results 21 to 30 of about 12,167 (257)
IEEE Access, 2023 Existing image processing methods usually divide image denoising and image fusion into two directions for research, and even the best current image denoising methods such as DnCNN can cause information loss during image processing, and the image fusion ...
Pengcheng Hu +4 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 +3 more
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IEEE Access, 2023 To improve the automatic classification accuracy of remote sensing images, this study raises a high-resolution remote sensing image classification model that combines deep transfer learning and multi-feature network. In this paper, deep transfer learning
Xinyan Huang
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Remote sensing image fusion via compressive sensing [PDF]
ISPRS Journal of Photogrammetry and Remote Sensing, 2019 Abstract In this paper, we propose a compressive sensing-based method to pan-sharpen the low-resolution multispectral (LRM) data, with the help of high-resolution panchromatic (HRP) data. In order to successfully implement the compressive sensing theory in pan-sharpening, two requirements should be satisfied: (i) forming a comprehensive dictionary in
Morteza Ghahremani +3 more
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Aggregating Features From Dual Paths for Remote Sensing Image Scene Classification
IEEE Access, 2022 Scene classification is an important and challenging task employed toward understanding remote sensing images. Convolutional neural networks have been widely applied in remote sensing scene classification in recent years, boosting classification accuracy.
Donghang Yu +5 more
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Multimodal Fusion Transformer for Remote Sensing Image Classification
IEEE Transactions on Geoscience and Remote Sensing, 2023 Vision transformers (ViTs) have been trending in image classification tasks due to their promising performance when compared to convolutional neural networks (CNNs). As a result, many researchers have tried to incorporate ViTs in hyperspectral image (HSI) classification tasks.
Roy, Swalpa Kumar +5 more
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Remote sensing image fusion: a practical guide [PDF]
Geo-spatial Information Science, 2017 Written by two of the best-known researchers in the field of remote sensing fusion, this book gives a good introduction to the subject of remote sensing image fusion.
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Remote Sensing, 2022 Remote sensing images with high temporal and spatial resolutions play a crucial role in land surface-change monitoring, vegetation monitoring, and natural disaster mapping.
Weisheng Li, Dongwen Cao, Minghao Xiang
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Decision Fusion for the Classification of Urban Remote Sensing Images [PDF]
IEEE Transactions on Geoscience and Remote Sensing, 2006 The classification of very high resolution remote sensing images from urban areas is addressed by considering the fusion of multiple classifiers which provide redundant or complementary results. The proposed fusion approach is in two steps. In a first step, data are processed by each classifier separately, and the algorithms provide for each pixel ...
Mathieu Fauvel +2 more
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Drones, 2023 Drone and aerial remote sensing images are widely used, but their imaging environment is complex and prone to image blurring. Existing CNN deblurring algorithms usually use multi-scale fusion to extract features in order to make full use of aerial remote
Baoyu Zhu, Qunbo Lv, Zheng Tan
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