[HTML][HTML] Deep learning in multimodal remote sensing data fusion: A comprehensive review
With the extremely rapid advances in remote sensing (RS) technology, a great quantity of
Earth observation (EO) data featuring considerable and complicated heterogeneity are …
Earth observation (EO) data featuring considerable and complicated heterogeneity are …
GeoAI for large-scale image analysis and machine vision: recent progress of artificial intelligence in geography
GeoAI, or geospatial artificial intelligence, has become a trending topic and the frontier for
spatial analytics in Geography. Although much progress has been made in exploring the …
spatial analytics in Geography. Although much progress has been made in exploring the …
Enhanced autoencoders with attention-embedded degradation learning for unsupervised hyperspectral image super-resolution
Recently, unmixing-based networks have shown significant potential in unsupervised
multispectral-aided hyperspectral image super-resolution (MS-aided HS-SR) task …
multispectral-aided hyperspectral image super-resolution (MS-aided HS-SR) task …
SSR-NET: Spatial–spectral reconstruction network for hyperspectral and multispectral image fusion
The fusion of a low-spatial-resolution hyperspectral image (HSI)(LR-HSI) with its
corresponding high-spatial-resolution multispectral image (MSI)(HR-MSI) to reconstruct a …
corresponding high-spatial-resolution multispectral image (MSI)(HR-MSI) to reconstruct a …
X-shaped interactive autoencoders with cross-modality mutual learning for unsupervised hyperspectral image super-resolution
Hyperspectral image super-resolution (HSI-SR) can compensate for the incompleteness of
single-sensor imaging and provide desirable products with both high spatial and spectral …
single-sensor imaging and provide desirable products with both high spatial and spectral …
Coupled convolutional neural network with adaptive response function learning for unsupervised hyperspectral super resolution
Due to the limitations of hyperspectral imaging systems, hyperspectral imagery (HSI) often
suffers from poor spatial resolution, thus hampering many applications of the imagery …
suffers from poor spatial resolution, thus hampering many applications of the imagery …
MCT-Net: Multi-hierarchical cross transformer for hyperspectral and multispectral image fusion
X Wang, X Wang, R Song, X Zhao, K Zhao - Knowledge-Based Systems, 2023 - Elsevier
Taking into account the limitations of optical imaging, image acquisition equipment is usually
designed to make a trade-off between spatial information and spectral information …
designed to make a trade-off between spatial information and spectral information …
Symmetrical feature propagation network for hyperspectral image super-resolution
Single hyperspectral image (HSI) super-resolution (SR) methods using a auxiliary high-
resolution (HR) RGB image have achieved great progress recently. However, most existing …
resolution (HR) RGB image have achieved great progress recently. However, most existing …
A deep framework for hyperspectral image fusion between different satellites
Recently, fusing a low-resolution hyperspectral image (LR-HSI) with a high-resolution
multispectral image (HR-MSI) of different satellites has become an effective way to improve …
multispectral image (HR-MSI) of different satellites has become an effective way to improve …
RGB-induced feature modulation network for hyperspectral image super-resolution
Super-resolution (SR) is one of the powerful techniques to improve image quality for low-
resolution (LR) hyperspectral image (HSI) with insufficient detail and noise. Traditional …
resolution (LR) hyperspectral image (HSI) with insufficient detail and noise. Traditional …