Search Results - Multispectral image fusion by convolutional autoencoder~

Convolutional Autoencoder-Based Multispectral Image Fusion

Authors: Arian Azarang Hafez E. Manoochehri Nasser Kehtarnavaz

Source: IEEE Access, Vol 7, Pp 35673-35683 (2019)

Subject Terms: 0211 other engineering and technologies, 0202 electrical engineering, electronic engineering, information engineering, Multispectral image fusion by convolutional autoencoder, Electrical engineering. Electronics. Nuclear engineering, 02 engineering and technology, fusion of panchromatic and multispectral images in remote sensing, convolutional autoencoder-based pansharpening, TK1-9971

Access URL: https://ieeexplore.ieee.org/ielx7/6287639/8600701/08668404.pdf
https://doaj.org/article/b66d1c75393749609de5a723b270824d
https://ieeexplore.ieee.org/document/8668404/
https://dblp.uni-trier.de/db/journals/access/access7.html#AzarangMK19

A Pansharpening Based on the Non-Subsampled Contourlet Transform and Convolutional Autoencoder: Application to QuickBird Imagery

Authors: Ahmad Al Smadi Shuyuan Yang Ahed Abugabah et al.

Source: IEEE Access, Vol 10, Pp 44778-44788 (2022)

Subject Terms: Technology, Science & Technology, multispectral image fusion, 0211 other engineering and technologies, NSCT, Pansharpening, 02 engineering and technology, convolutional autoencoder, TK1-9971, remote sensing, Engineering, Computer Science, Telecommunications, 0202 electrical engineering, electronic engineering, information engineering, Nanotechnology, Electrical & Electronic, Electrical engineering. Electronics. Nuclear engineering, Information Systems

Access URL: https://doaj.org/article/34ee88da446440829ab7702d7885f6da

Multiscale spatial–spectral transformer network for hyperspectral and multispectral image fusion.

Authors: Jia, Sen Min, Zhichao Fu, Xiyou

Source: Information Fusion. Aug2023, Vol. 96, p117-129. 13p.

Subject Terms: *MULTISPECTRAL imaging, *IMAGE fusion, *CONVOLUTIONAL neural networks, *FEATURE extraction, *SPATIAL resolution, *NETWORK performance

An Improved Pan-Sharpening Method Based on Convolutional Autoencoder and Guided Filter (CAE-GF) on Quickbird Images.

Alternate Title: Um Método Aprimorado de Pan-Sharpening Baseado em Autoencoder Convolucional e Filtro Guiado (CAE-FG) em Imagens Quickbird. (Portuguese)

Authors: da Silva Costa, Jessica Araki, Hideo

Source: Anuário do Instituto de Geociências; 2024, Vol. 47, p1-13, 13p

Subject Terms: AUTOENCODERS, DEEP learning, REMOTE sensing, IMAGE fusion

FusionNet: An Unsupervised Convolutional Variational Network for Hyperspectral and Multispectral Image Fusion.

Authors: Wang, Zhengjue Chen, Bo Lu, Ruiying et al.

Source: IEEE Transactions on Image Processing. 2020, Vol. 29, p7565-7577. 13p.

Subject Terms: *MULTISPECTRAL imaging, *IMAGE fusion, *CONVOLUTIONAL neural networks, *HIGH resolution imaging, *SPECTRAL imaging, *PROBABILISTIC generative models

CAEFusion: A New Convolutional Autoencoder-Based Infrared and Visible Light Image Fusion Algorithm.

Authors: Wu, Chun-Ming Ren, Mei-Ling Lei, Jin et al.

Source: Computers, Materials & Continua; 2024, Vol. 80 Issue 2, p2857-2872, 16p

Subject Terms: OBJECT recognition (Computer vision), IMAGE fusion, INFRARED imaging, VISIBLE spectra, DEEP learning

KANDiff: Kolmogorov–Arnold Network and Diffusion Model-Based Network for Hyperspectral and Multispectral Image Fusion.

Authors: Li, Wei Li, Lu Peng, Man et al.

Source: Remote Sensing; Jan2025, Vol. 17 Issue 1, p145, 25p

Subject Terms: REMOTE sensing, IMAGE processing, CONVOLUTIONAL neural networks, LUNAR surface, SIGNAL-to-noise ratio, IMAGE fusion

FCSwinU: Fourier Convolutions and Swin Transformer UNet for Hyperspectral and Multispectral Image Fusion.

Authors: Li, Rumei Zhang, Liyan Wang, Zun et al.

Source: Sensors (14248220); Nov2024, Vol. 24 Issue 21, p7023, 20p

Subject Terms: TRANSFORMER models, IMAGE fusion, CONVOLUTIONAL neural networks, DEEP learning, FEATURE extraction, MULTISPECTRAL imaging

Dual-pyramid framework for robust infrared-visible image registration and fusion via convolutional dictionary learning.

Authors: Wu, Chaojie Li, Zheng

Source: Visual Computer; Dec2025, Vol. 41 Issue 15, p12743-12764, 22p

Subject Terms: IMAGE registration, IMAGE fusion, INFRARED imaging, MACHINE learning, DEEP learning, IMAGE processing

Convolutional Autoencoder-Based Multispectral Image Fusion

Authors: Azarang, Arian Manoochehri, Hafez E. Kehtarnavaz, Nasser et al.

Contributors: Azarang, Arian Manoochehri, Hafez E. Kehtarnavaz, Nasser et al.

Source: IEEE Access

Subject Terms: Convolutions (Mathematics), Deep learning, Remote sensing, Multispectral imaging

File Description: application/pdf

Relation: https://dx.doi.org/10.1109/ACCESS.2019.2905511; https://hdl.handle.net/10735.1/7050

Availability: https://hdl.handle.net/10735.1/7050

Self-supervised spectral super-resolution for a fast hyperspectral and multispectral image fusion.

Authors: Rajaei, Arash Abiri, Ebrahim Helfroush, Mohammad Sadegh

Source: Scientific Reports; 11/30/2024, Vol. 14 Issue 1, p1-15, 15p

Subject Terms: ARTIFICIAL neural networks, IMAGE fusion, DEEP learning, REMOTE sensing, SOURCE code, MULTISPECTRAL imaging

An Improved Pan-Sharpening Method Based on Convolutional Autoencoder and Guided Filter (CAE-GF) on Quickbird Images

Authors: Costa, Jessica da Silva Araki, Hideo

Source: Anuário do Instituto de Geociências, Volume: 47, Article number: 58601, Published: 25 AUG 2025. August 2025

Subject Terms: Deep learning, Image fusion, Remote sensing, Fusão de imagens, Sensoriamento remoto

File Description: text/html

Access URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1982-39082024000100301&lng=en&tlng=en

A model-guided deep convolutional sparse coding network for hyperspectral and multispectral image fusion.

Authors: Khader, Abdolraheem Xiao, Liang Yang, Jingxiang

Source: International Journal of Remote Sensing; Mar2022, Vol. 43 Issue 6, p2268-2295, 28p

Subject Terms: MULTISPECTRAL imaging, IMAGE fusion, DEEP learning, LINEAR network coding, THRESHOLDING algorithms, HIGH resolution imaging, SYLVESTER matrix equations

Company/Entity: HARVARD University

Novel Cross-Resolution Feature-Level Fusion for Joint Classification of Multispectral and Panchromatic Remote Sensing Images.

Authors: Liu, Sicong Zhao, Hui Du, Qian et al.

Source: IEEE Transactions on Geoscience & Remote Sensing. Apr2022, Vol. 60, p1-14. 14p.

Subject Terms: MULTISPECTRAL imaging, REMOTE sensing, CONVOLUTIONAL neural networks, CLASSIFICATION

An Unmixing-Based Multi-Attention GAN for Unsupervised Hyperspectral and Multispectral Image Fusion.

Authors: Su, Lijuan Sui, Yuxiao Yuan, Yan

Source: Remote Sensing; Feb2023, Vol. 15 Issue 4, p936, 22p

Subject Terms: IMAGE fusion, MULTISPECTRAL imaging, GENERATIVE adversarial networks, HIGH resolution imaging, SPATIAL resolution

A General Paradigm with Detail-Preserving Conditional Invertible Network for Image Fusion.

Authors: Wang, Wu Deng, Liang-Jian Ran, Ran et al.

Source: International Journal of Computer Vision; Apr2024, Vol. 132 Issue 4, p1029-1054, 26p

Subject Terms: IMAGE fusion, INFRARED imaging, MULTISPECTRAL imaging, BENCHMARK problems (Computer science), DEEP learning, REMOTE sensing

Pansharpening based on convolutional autoencoder and multi-scale guided filter.

Authors: AL Smadi, Ahmad Yang, Shuyuan Kai, Zhang et al.

Source: EURASIP Journal on Image & Video Processing; 7/19/2021, Vol. 2021 Issue 1, p1-20, 20p

Subject Terms: MULTISPECTRAL imaging, CONVOLUTIONAL neural networks, REMOTE sensing, IMAGE reconstruction

A Systematic Literature Review on Multimodal Image Fusion Models with Challenges and Future Research Trends.

Authors: Ravi, Jampani Narmadha, R.

Source: International Journal of Image & Graphics; Jul2025, Vol. 25 Issue 4, p1-33, 33p

Multi spectral image fusion by deep convolutional neural network and new spectral loss function.

Authors: Eghbalian, Sajjad Ghassemian, Hassan

Source: International Journal of Remote Sensing; Jun2018, Vol. 39 Issue 12, p3983-4002, 20p, 4 Diagrams, 6 Charts

Subject Terms: IMAGE fusion, ARTIFICIAL neural networks, MULTISPECTRAL imaging, BANDWIDTHS, MULTIPLE correspondence analysis (Statistics)

Model-based Bayesian Fusion-Net for infrared and visible image fusion.

Authors: Li, Wang Yafang, Kuang Ziyi, Cai et al.

Source: EURASIP Journal on Image & Video Processing; 8/6/2025, Vol. 2025 Issue 1, p1-25, 25p

Subject Terms: IMAGE fusion, INFRARED photography, COMPUTATIONAL complexity, QUANTITATIVE research, IMAGE processing