Results 31 to 40 of about 1,803 (195)
SC-PNN: Saliency Cascade Convolutional Neural Network for Pansharpening
, 2021 In many remote sensing tasks, different types of regions or targets differ in requirements for spectral and spatial quality. The discrepancy reveals that a uniform pansharpening strategy applying to the entire image may not fulfill the varying demands of
Zhang, Jue +3 more
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THE EFFECT OF PANSHARPENING ALGORITHMS ON THE RESULTING ORTHOIMAGERY [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2016 This paper evaluates the geometric effects of pansharpening algorithms on automatically generated DSMs and thus on the resulting orthoimagery through a quantitative assessment of the accuracy on the end products. The main motivation was based on the fact
P. Agrafiotis +2 more
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Multi-resolution, multi-sensor image fusion: general fusion framework [PDF]
, 2011 Multi-resolution image fusion also known as pansharpening aims to include spatial information from a high resolution image, e.g. panchromatic or Synthetic Aperture Radar (SAR) image, into a low resolution image, e.g.
Palubinskas, Gintautas +3 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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IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2022 Hyperspectral (HS) pansharpening aims at fusing a low-resolution HS image with a high-resolution panchromatic (PAN) image to obtain a HS image with both higher spectral and spatial resolutions.
Yu-Wei Zhuo +5 more
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On the validation of pansharpening methods
CoRR, 2021 Validation of the quality of pansharpening methods is a difficult task because the reference is not directly available. In the meantime, two main approaches have been established: validation in reduced resolution and original resolution. In the former approach it is still not clear how the data are to be processed to a lower resolution.
openaire +3 more sources
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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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. +9 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
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