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Spectral Diversity Enhancement for Pansharpening

2018 25th IEEE International Conference on Image Processing (ICIP), 2018
Pansharpening is to generate a synthetic image with high spatial resolution and high spectral resolution via fusing panchromatic (PAN) and multispectral (MS) images. In most traditional pansharpening methods, the original MS image is firstly interpolated to the same size of PAN image by analytical interpolations.
Liangyu Zhou   +3 more
openaire   +1 more source

High-Fidelity Pansharpening via Trigeminal Pyramid Decoding of CNN-Transformer Encoded Features

IEEE Transactions on Geoscience and Remote Sensing
Spectral and spatial fidelity remains a longstanding challenge in the field of pansharpening, which aims to generate high-resolution multispectral (HRMS) images by integrating high-resolution panchromatic (PAN) images with low-resolution multispectral ...
Lihui Chen   +5 more
semanticscholar   +1 more source

A Novel Spectral-Spatial Attention Network for Zero-Shot Pansharpening

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Over the past decades, pansharpening technologies have received much attention due to the spatial detail enhancement they introduce into multispectral (MS) images by referencing them to panchromatic images (PAN).
Hailiang Lu   +5 more
semanticscholar   +1 more source

Zero-Shot Hyperspectral Pansharpening Using Hysteresis-Based Tuning for Spectral Quality Control

IEEE Transactions on Geoscience and Remote Sensing
Hyperspectral (HS) pansharpening has received much attention in recent years due to technological and methodological advances that open the door to new application scenarios. However, research on this topic is only now gaining momentum.
Giuseppe Guarino   +4 more
semanticscholar   +1 more source

Hyperspectral Pansharpening via Diffusion Models with Iteratively Zero-Shot Guidance

Computer Vision and Pattern Recognition
Hyperspectral pansharpening refers to fusing a panchromatic image (PAN) and a low-resolution hyperspectral image (LR-HSI) to obtain a high-resolution hyperspectral image (HR-HSI).
Jin-Liang Xiao   +6 more
semanticscholar   +1 more source

Empower Generalizability for Pansharpening Through Text-Modulated Diffusion Model

IEEE Transactions on Geoscience and Remote Sensing
Pansharpening is crucial to remote sensing applications by fusing high-resolution (HR) panchromatic (PAN) images with low-resolution multispectral (LRMS) images to generate HR multispectral (HRMS) images.
Yinghui Xing   +5 more
semanticscholar   +1 more source

Affinity Pansharpening and Image Fusion

2014 International Conference on Digital Image Computing: Techniques and Applications (DICTA), 2014
A novel framework for enhancing the resolution of a low-resolution multispectral or hyperspectral image using a high resolution panchromatic image or multispectral image is proposed in this paper. This framework can be further used to perform more general types of image fusion.
Stephen Tierney, Junbin Gao, Yi Guo
openaire   +1 more source

Dual-Granularity Semantic Guided Sparse Routing Diffusion Model for General Pansharpening

Computer Vision and Pattern Recognition
Pansharpening aims at integrating complementary information from panchromatic and multispectral images. Available deep-learning based pansharpening methods typically perform exceptionally with particular satellite datasets.
Yinghui Xing   +5 more
semanticscholar   +1 more source

Taming Flow Matching with Unbalanced Optimal Transport into Fast Pansharpening

arXiv.org
Pansharpening, a pivotal task in remote sensing for fusing high-resolution panchromatic and multispectral imagery, has garnered significant research interest. Recent advancements employing diffusion models based on stochastic differential equations (SDEs)
Zihan Cao, Yu Zhong, Liang-Jian Deng
semanticscholar   +1 more source

Cross-Modal Contrastive Pansharpening via Uncertainty Guidance

IEEE Transactions on Geoscience and Remote Sensing
Deep learning (DL)-based pansharpening has been widely applied in high-resolution imaging. Yet, artifacts related to generalization and oversmoothing have continuously been the challenge, primarily due to the mismatch between the simulation dataset and ...
Haoying Zeng   +5 more
semanticscholar   +1 more source

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