Search Results - convolutional autoencoder-based pansharpening

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

Pansharpening Techniques: Optimizing the Loss Function for Convolutional Neural Networks.

Authors: Restaino, Rocco

Source: Remote Sensing; Jan2025, Vol. 17 Issue 1, p16, 30p

Subject Terms: CONVOLUTIONAL neural networks, COST functions, SURFACE of the earth, IMAGE fusion, MULTISPECTRAL imaging

Pansharpening scheme using spatial detail injection–based convolutional neural networks.

Authors: Saxena, Nidhi Saxena, Gaurav Khare, Neelu et al.

Source: IET Image Processing (Wiley-Blackwell); Jul2022, Vol. 16 Issue 9, p2297-2307, 11p

Subject Terms: CONVOLUTIONAL neural networks, MULTISPECTRAL imaging, REMOTE-sensing images, IMAGE registration

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

Detail Injection-Based Deep Convolutional Neural Networks for Pansharpening.

Authors: Deng, Liang-Jian Vivone, Gemine Jin, Cheng et al.

Source: IEEE Transactions on Geoscience & Remote Sensing; Aug2021, Vol. 59 Issue 8, p6995-7010, 16p

Subject Terms: CONVOLUTIONAL neural networks, MACHINE learning, SPATIAL resolution

A pansharpening scheme using spectral graph wavelet transforms and convolutional neural networks.

Authors: Saxena, Nidhi Balasubramanian, Raman

Source: International Journal of Remote Sensing; Apr2021, Vol. 42 Issue 8, p2898-2919, 22p

Subject Terms: CONVOLUTIONAL neural networks, ARTIFICIAL neural networks, WAVELET transforms

Pansharpening Scheme Using Bi-dimensional Empirical Mode Decomposition and Neural Network.

Authors: SAXENA, NIDHI RAMAN, BALASUBRAMANIAN

Source: ACM Transactions on Multimedia Computing, Communications & Applications; Oct2022, Vol. 18 Issue 4, p1-22, 22p

Subject Terms: HILBERT-Huang transform, REMOTE-sensing images, CONVOLUTIONAL neural networks

Pansharpening with multi-CAE: impact of patch size and overlapping pixels on spectral and spatial distortion.

Authors: Al Smadi, Ahmad Abugabah, Ahed Alsmadi, Mutasem Khlail et al.

Source: Telkomnika; Aug2024, Vol. 22 Issue 4, p985-994, 10p

Subject Terms: MULTISPECTRAL imaging, SPECTRAL imaging, PIXELS, REMOTE sensing, SPATIAL resolution, COSMIC background radiation

A Graph-Based Superpixel Segmentation Approach Applied to Pansharpening.

Authors: Hallabia, Hind

Source: Sensors (14248220); Aug2025, Vol. 25 Issue 16, p4992, 25p

Subject Terms: IMAGE fusion, IMAGE segmentation, SIMPLEX algorithm, GEOSPATIAL data, MULTISENSOR data fusion, MULTISPECTRAL imaging, HIGH resolution imaging

A Novel Convolutional Autoencoder-Based Clutter Removal Method for Buried Threat Detection in Ground-Penetrating Radar.

Authors: Temlioglu, Eyyup Erer, Isin

Source: IEEE Transactions on Geoscience & Remote Sensing; Jan2022, Vol. 60 Issue 1, p1-13, 13p

Subject Terms: GROUND penetrating radar, MATRIX decomposition, NONNEGATIVE matrices, SPARSE matrices, IMAGE reconstruction, NOISE control

Recent Advances in Deep Learning-Based Spatiotemporal Fusion Methods for Remote Sensing Images.

Authors: Lian, Zilong Zhan, Yulin Zhang, Wenhao et al.

Source: Sensors (14248220); Feb2025, Vol. 25 Issue 4, p1093, 34p

Subject Terms: GENERATIVE adversarial networks, CONVOLUTIONAL neural networks, REMOTE sensing, COMPUTER science, TRANSFORMER models, DEEP learning

Vector-Quantized Variational AutoEncoder for pansharpening.

Authors: Talbi, Farid Elmezouar, Miloud Chikr Boutellaa, Elhocine et al.

Source: International Journal of Remote Sensing; Oct2023, Vol. 44 Issue 20, p6329-6349, 21p

Subject Terms: MULTISPECTRAL imaging, SPATIAL resolution, SPECTRAL imaging, IMAGE fusion, CITIES & towns, THEMATIC mapper satellite

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

MBSFC: hyperspectral image classification based on multi-branch and spectral feature conversion.

Authors: Tang, Ting Liu, Shaopeng Fu, Xueliang et al.

Source: International Journal of Remote Sensing; Nov2024, Vol. 45 Issue 22, p8202-8229, 28p

Subject Terms: CONVOLUTIONAL neural networks, IMAGE recognition (Computer vision), FEATURE extraction, DEEP learning, REMOTE sensing

Learning Deep Pyramid-based Representations for Pansharpening.

Authors: Adeel, Hannan Ali, Syed Sohaib Riaz, Muhammad Mohsin et al.

Source: Arabian Journal for Science & Engineering (Springer Science & Business Media B.V. ); Aug2022, Vol. 47 Issue 8, p10655-10666, 12p

Subject Terms: DEEP learning, MULTISPECTRAL imaging, IMAGE fusion, STATISTICAL correlation, PYRAMIDS

Airborne and Spaceborne Hyperspectral Remote Sensing in Urban Areas: Methods, Applications, and Trends.

Authors: Gámez García, José Antonio Lazzeri, Giacomo Tapete, Deodato

Source: Remote Sensing; Sep2025, Vol. 17 Issue 17, p3126, 40p

Subject Terms: MACHINE learning, REMOTE sensing, CITIES & towns, MULTISENSOR data fusion, DEEP learning, AERIAL photogrammetry, HYPERSPECTRAL imaging systems, URBAN research

Monitoring Desertification in Adrar Algeria Using Deep Learning and Spectral Indexes with Landsat-8 Images.

Authors: Abdelwhab, Ouahab

Source: Optoelectronics Instrumentation & Data Processing; Feb2025, Vol. 61 Issue 1, p112-118, 7p

SUPER-RESOLUTION OF MULTISPECTRAL SATELLITE IMAGES USING CONVOLUTIONAL NEURAL NETWORKS.

Authors: Müller, M. U. Ekhtiari, N. Almeida, R. M. et al.

Source: ISPRS Annals of Photogrammetry, Remote Sensing & Spatial Information Sciences; 2020, Vol. 5 Issue 1, p33-40, 8p

Subject Terms: MULTISPECTRAL imaging, CONVOLUTIONAL neural networks, REMOTE-sensing images, COMPUTER vision, REMOTE sensing, VISUAL fields

CCC-SSA-UNet: U-Shaped Pansharpening Network with Channel Cross-Concatenation and Spatial–Spectral Attention Mechanism for Hyperspectral Image Super-Resolution.

Authors: Liu, Zhichao Han, Guangliang Yang, Hang et al.

Source: Remote Sensing; Sep2023, Vol. 15 Issue 17, p4328, 34p

Subject Terms: HIGH resolution imaging, IMAGE fusion, MULTISPECTRAL imaging, SPATIAL ability, SPATIAL resolution, COMPUTATIONAL complexity, IMAGE reconstruction algorithms

Hyperspectral Image Super Resolution Using Anomaly Weighted Gabor Based CNN.

Authors: Farajzadeh, Ali Imani, Maryam Mohammadi, Shahram

Source: International Journal of Information & Communication Technology Research (2251-6107); 2023, Vol. 15 Issue 2, p19-28, 10p

Subject Terms: HYPERSPECTRAL imaging systems, CONVOLUTIONAL neural networks, DEEP learning, HIGH resolution imaging, SPATIAL resolution, GABOR filters, PIXELS, ANOMALY detection (Computer security)