Diffusion model with disentangled modulations for sharpening multispectral and hyperspectral images
The denoising diffusion model has received increasing attention in the field of image
generation in recent years, thanks to its powerful generation capability. However, diffusion …
generation in recent years, thanks to its powerful generation capability. However, diffusion …
HD-Net: High-resolution decoupled network for building footprint extraction via deeply supervised body and boundary decomposition
The extraction of building footprints, as a highly challenging task in remote sensing (RS)
image-based geospatial object detection and recognition, holds significant importance. Due …
image-based geospatial object detection and recognition, holds significant importance. Due …
Hyperspectral Pansharpening: Critical review, tools, and future perspectives
Hyperspectral (HS) pansharpening consists of fusing a high-resolution panchromatic (PAN)
band and a low-resolution HS image to obtain a new image with high resolution in both the …
band and a low-resolution HS image to obtain a new image with high resolution in both the …
Weakly supervised low-rank representation for hyperspectral anomaly detection
In this article, we propose a weakly supervised low-rank representation (WSLRR) method for
hyperspectral anomaly detection (HAD), which formulates deep learning-based HAD into a …
hyperspectral anomaly detection (HAD), which formulates deep learning-based HAD into a …
A dual-branch detail extraction network for hyperspectral pansharpening
Hyperspectral (HS) pansharpening aims at creating a high-resolution hyperspectral (HR-
HS) image by integrating a high spatial resolution panchromatic (HR-PAN) image with a low …
HS) image by integrating a high spatial resolution panchromatic (HR-PAN) image with a low …
A latent encoder coupled generative adversarial network (le-gan) for efficient hyperspectral image super-resolution
Realistic hyperspectral image (HSI) super-resolution (SR) techniques aim to generate a high-
resolution (HR) HSI with higher spectral and spatial fidelity from its low-resolution (LR) …
resolution (HR) HSI with higher spectral and spatial fidelity from its low-resolution (LR) …
Panchromatic and hyperspectral image fusion: Outcome of the 2022 WHISPERS hyperspectral pansharpening challenge
This article presents the scientific outcomes of the 2022 Hyperspectral Pansharpening
Challenge organized by the 12th IEEE Workshop on Hyperspectral Image and Signal …
Challenge organized by the 12th IEEE Workshop on Hyperspectral Image and Signal …
HyperPNN: Hyperspectral pansharpening via spectrally predictive convolutional neural networks
Hyperspectral (HS) pansharpening intends to synthesize a HS image with a registered
panchromatic image, to generate an enhanced image with simultaneous high spectral …
panchromatic image, to generate an enhanced image with simultaneous high spectral …
Joint filtering of intensity images and neuromorphic events for high-resolution noise-robust imaging
We present a novel computational imaging system with high resolution and low noise. Our
system consists of a traditional video camera which captures high-resolution intensity …
system consists of a traditional video camera which captures high-resolution intensity …
Hyperspectral image classification: An analysis employing CNN, LSTM, transformer, and attention mechanism
Hyperspectral images contain tens to hundreds of bands, implying a high spectral
resolution. This high spectral resolution allows for obtaining a precise signature of structures …
resolution. This high spectral resolution allows for obtaining a precise signature of structures …