Results 211 to 220 of about 4,917 (234)
Some of the next articles are maybe not open access.
Quantitative analysis of pansharpened images
Optical Engineering, 2006Pansharpening is a pixel-level fusion technique used to increase the spatial resolution of the multispectral image using spatial information from the high-resolution panchromatic image, while preserving the spectral information in the multispectral image.
openaire +1 more source
Exploring Text-Guided Information Fusion Through Chain-of-Reasoning for Pansharpening
IEEE Transactions on Geoscience and Remote SensingPansharpening aims to enhance the spatial resolution of low-resolution multispectral (LRMS) images by integrating high-frequency information from a corresponding texture-rich panchromatic (PAN) image, while maintaining the spectral integrity of the LRMS ...
Xueheng Li +7 more
semanticscholar +1 more source
Vision Transformer for Pansharpening
IEEE Transactions on Geoscience and Remote Sensing, 2022Xiangchao Meng +3 more
openaire +1 more source
IEEE Transactions on Geoscience and Remote Sensing
Multitask learning (MTL) serves as an effective technology to improve both the performance of hyperspectral image (HSI) pansharpening and that of downstream classification tasks.
Shaoxiong Hou +3 more
semanticscholar +1 more source
Multitask learning (MTL) serves as an effective technology to improve both the performance of hyperspectral image (HSI) pansharpening and that of downstream classification tasks.
Shaoxiong Hou +3 more
semanticscholar +1 more source
Feature Pyramid Fusion Network for Hyperspectral Pansharpening
IEEE Transactions on Neural Networks and Learning SystemsHyperspectral (HS) pansharpening aims at fusing an observed HS image with a panchromatic (PAN) image, to produce an image with the high spectral resolution of the former and the high spatial resolution of the latter. Most of the existing convolutional neural networks (CNNs)-based pansharpening methods reconstruct the desired high-resolution image from ...
Wenqian Dong +5 more
openaire +2 more sources
YUV Color Model-Based Adaptive Pansharpening with Lanczos Interpolation and Spectral Weights
MathematicsPansharpening is a method of image fusion that combines a panchromatic (PAN) image with high spatial resolution and multispectral (MS) images which possess different spectral characteristics and are frequently obtained from satellite sensors. Despite the
Shavkat Fazilov +4 more
semanticscholar +1 more source
DCPNet: A Dual-Task Collaborative Promotion Network for Pansharpening
IEEE Transactions on Geoscience and Remote SensingPansharpening, a type of image fusion, combines a high-resolution panchromatic (PAN) image with a low-resolution multispectral (LRMS) image to produce a high-resolution multispectral (HRMS) output.
Yafei Zhang +4 more
semanticscholar +1 more source
Atmospheric corrections for pansharpening
2017Among remote sensing image fusion applications, panchromatic (Pan) sharpening, or pansharpening, of a multispectral (MS) image has received considerable attention over the last quarter of century. Pansharpening techniques take advantage of the complementary characteristics of spatial and spectral resolutions of MS and Pan data, in order to synthesize a
Luciano Alparone +3 more
openaire +1 more source
IEEE Transactions on Geoscience and Remote Sensing
Pan-sharpening refers to fusing remote sensing multispectral (MS) and panchromatic (PAN) images to generate high-resolution multispectral (HR-MS) images.
Yifan Meng +7 more
semanticscholar +1 more source
Pan-sharpening refers to fusing remote sensing multispectral (MS) and panchromatic (PAN) images to generate high-resolution multispectral (HR-MS) images.
Yifan Meng +7 more
semanticscholar +1 more source
Deep Unfolding Tensor Rank Minimization With Generalized Detail Injection for Pansharpening
IEEE Transactions on Geoscience and Remote SensingPansharpening aims to generate a high-resolution multispectral (HRMS) image by merging a low-resolution multispectral (LRMS) image with a high-resolution panchromatic (PAN) image.
Truong Thanh Nhat Mai, E. Lam, Chul Lee
semanticscholar +1 more source

