Results 31 to 40 of about 1,701 (201)
QNR Optimization based Pansharpening [PDF]
IGARSS 2008 - 2008 IEEE International Geoscience and Remote Sensing Symposium, 2008 Quality Without Reference (QNR) index can be used to globally assess the quality of pansharpened images without the need of a reference high resolution multispectral (MS) image. The QNR index relies on local calculation of the Q4 index. Exploiting the local Q4 calculation property of the QNR index, we propose an injection model for pansharpening.
Muhammad Murtaza Khan +2 more
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Multispectral Pansharpening Based on Multisequence Convolutional Recurrent Neural Network
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2022 Multispectral (MS) pansharpening is defined as the fusion of spatial information in panchromatic (PAN) image and spectral information in MS image. In this work, we propose an MS pansharpening based on multisequence convolutional recurrent neural network (
Peng Wang +5 more
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AESGGAN: an attention embedded adversarial network for pansharpening
四川大学学报. 自然科学版, 2023 Pansharpening aims to fuse low-resolution multispectral image with high-resolution panchromatic image to generate a high-resolution multispectral image. With the development of Convolutional Neural Network (CNN), many CNN-based pansharpening methods have
ZHANG Pan, LI Xiao-Hua, ZHOU Ji-Liu
doaj
Remote Sensing, 2017 The objective of this work is to develop an algorithm for pansharpening of very high resolution (VHR) satellite imagery that reduces the spectral distortion of the pansharpened images and enhances their spatial clarity with minimal computational costs ...
Jaewan Choi +4 more
doaj +1 more source
An Unsupervised CNN-Based Hyperspectral Pansharpening Method
, 2023 This work proposes a simple yet effective method to adapt unsupervised convolutional neural networks for pansharpening of multispectral images to the problem of hyperspectral image pansharpening, i.e., the fusion of a single high-resolution panchromatic ...
Scarpa G. +4 more
core +1 more source
Pansharpening by Combining Enhanced Spatial-Spectral Fidelity and Gradient-Domain Guided Filtering
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2023 Pansharpening techniques fuse the complementary information from a high-resolution panchromatic (PAN) and low-resolution multispectral (LRMS) images to produce a high-resolution multispectral (HRMS) image.
Li Liu +3 more
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Full-Resolution Quality Assessment for Pansharpening
Remote Sensing, 2022 A reliable quality assessment procedure for pansharpening methods is of critical importance for the development of the related solutions. Unfortunately, the lack of ground truths to be used as guidance for an objective evaluation has pushed the community to resort to two approaches, which can also be jointly applied.
Giuseppe Scarpa, Matteo Ciotola
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Quality assessment by region in spot images fused by means dual-tree complex wavelet transform [PDF]
, 2011 This work is motivated in providing and evaluating a fusion algorithm of remotely sensed images, i.e. the fusion of a high spatial resolution panchromatic image with a multi-spectral image (also known as pansharpening) using the dual-tree complex wavelet
Arquero Hidalgo, Águeda +2 more
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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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A Local and Nonlocal Feature Interaction Network for Pansharpening
Remote Sensing, 2022 Pansharpening based on deep learning (DL) has shown great advantages. Most convolutional neural network (CNN)-based methods focus on obtaining local features from multispectral (MS) and panchromatic (PAN) images, but ignore the nonlocal dependence on ...
Junru Yin +4 more
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