Results 21 to 30 of about 1,803 (195)
Pansharpening Using Guided Filtering to Improve the Spatial Clarity of VHR Satellite Imagery
Remote Sensing, 2019 Pansharpening algorithms are designed to enhance the spatial resolution of multispectral images using panchromatic images with high spatial resolutions. Panchromatic and multispectral images acquired from very high resolution (VHR) satellite sensors used
Jaewan Choi, Honglyun Park, Doochun Seo
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Optimal pansharpening of RASAT satellite imagery
2014 22nd Signal Processing and Communications Applications Conference (SIU), 2014 Pansharpening is a pixel-level fusion technique for increasing the spatial resolution of low-resolution multi-spectral satellite imagery using high resolution panchromatic imagery. In this work, the performance of various pan sharpening algorithms in improving the 7.5 meter resolution of RASAT satellite imagery is compared Nine different pansharpening ...
Mustafa Teke 0001 +3 more
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Pansharpening via Multiscale Embedding and Dual Attention Transformers
IEEE Journal of Selected Topics in Applied Earth Observations and Remote SensingPansharpening is a fundamental and crucial image processing task for many remote sensing applications, which generates a high-resolution multispectral image by fusing a low-resolution multispectral image and a high-resolution panchromatic image. Recently,
Wensheng Fan, Fan Liu, Jingzhi Li
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An Adaptive Injection Model for Pansharpening. [PDF]
Comput Intell Neurosci, 2023 Pansharpening technology is used to acquire a multispectral image with high spatial resolution from a panchromatic (PAN) image and a multispectral (MS) image. The detail injection model is popular for its flexibility. However, the accuracy of the injection gain and the extracted details may greatly influence the quality of the pansharpened image.
Song Q, Ding C, Ren J, Liu L, Lu H.
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Tree-Structured Neural Network for Hyperspectral Pansharpening
IEEE Journal of Selected Topics in Applied Earth Observations and Remote SensingHyperspectral (HS) pansharpening refers to fusing low spatial resolution HS (LRHS) images with the corresponding panchromatic (PAN) images to create high spatial resolution HS (HRHS) images.
Lin He +5 more
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ZSBP: Zero-Shot Semi-Supervised Learning for Blind Pansharpening
IEEE Journal of Selected Topics in Applied Earth Observations and Remote SensingPansharpening aims to generate high-resolution multispectral images (HRMS) by effectively leveraging the complementary information in high-resolution panchromatic images (HRPan) and low-resolution multispectral images (LRMS).
Jialei Xie +5 more
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Cross-Modal Information Aggregation Network With Feature Enhancement for Pansharpening
IEEE Journal of Selected Topics in Applied Earth Observations and Remote SensingPansharpening is a vital process that aims to obtain high-resolution multispectral (HRMS) images by fusing panchromatic (PAN) and low-resolution multispectral images. With the advancement of deep learning (DL), data-driven pansharpening methods have been
Lihua Jian +3 more
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No Reference Pansharpened Image Quality Assessment Through Deep Feature Similarity
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2022 Pansharpening refers to the process of enhancing the spatial resolution of a multispectral image with the help of a high spatial resolution panchromatic (PAN) image.
Neeraj Badal +3 more
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ISPRS Open Journal of Photogrammetry and Remote Sensing, 2023 The compatibility of multispectral (MS) pansharpening algorithms with hyperspectral (HS) data is limited. With the recent development in HS satellites, there is a need for methods that can provide high spatial and spectral fidelity in both HS and MS ...
Tuomas Sihvonen +3 more
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Pansharpening by Convolutional Neural Networks [PDF]
Remote Sensing, 2016 A new pansharpening method is proposed, based on convolutional neural networks. We adapt a simple and effective three-layer architecture recently proposed for super-resolution to the pansharpening problem. Moreover, to improve performance without increasing complexity, we augment the input by including several maps of nonlinear radiometric indices ...
MASI, GIUSEPPE +3 more
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