A Sparse Image Fusion Algorithm With Application to Pan-Sharpening
Xiao Xiang Zhu,Richard Bamler +1 more
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TLDR
This paper proposes a new pan-sharpening method named SparseFI, based on the compressive sensing theory and explores the sparse representation of HR/LR multispectral image patches in the dictionary pairs cotrained from the panchromatic image and its downsampled LR version.Abstract:
Data provided by most optical Earth observation satellites such as IKONOS, QuickBird, and GeoEye are composed of a panchromatic channel of high spatial resolution (HR) and several multispectral channels at a lower spatial resolution (LR). The fusion of an HR panchromatic and the corresponding LR spectral channels is called “pan-sharpening.” It aims at obtaining an HR multispectral image. In this paper, we propose a new pan-sharpening method named Sparse F usion of Images (SparseFI, pronounced as “sparsify”). SparseFI is based on the compressive sensing theory and explores the sparse representation of HR/LR multispectral image patches in the dictionary pairs cotrained from the panchromatic image and its downsampled LR version. Compared with conventional methods, it “learns” from, i.e., adapts itself to, the data and has generally better performance than existing methods. Due to the fact that the SparseFI method does not assume any spectral composition model of the panchromatic image and due to the super-resolution capability and robustness of sparse signal reconstruction algorithms, it gives higher spatial resolution and, in most cases, less spectral distortion compared with the conventional methods.read more
Citations
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Journal ArticleDOI
A Critical Comparison Among Pansharpening Algorithms
Gemine Vivone,Luciano Alparone,Jocelyn Chanussot,Mauro Dalla Mura,Andrea Garzelli,Giorgio Licciardi,Rocco Restaino,Lucien Wald +7 more
TL;DR: The authors attempt to fill the gap by providing a critical description and extensive comparisons of some of the main state-of-the-art pansharpening methods by offering a detailed comparison of their performances with respect to the different instruments.
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Pixel-level image fusion
TL;DR: It is concluded that although various image fusion methods have been proposed, there still exist several future directions in different image fusion applications and the researches in the image fusion field are still expected to significantly grow in the coming years.
Journal ArticleDOI
Pansharpening by Convolutional Neural Networks
TL;DR: A new pansharpening method is proposed, based on convolutional neural networks, which is largely competitive with the current state of the art in terms of both full-reference and no-reference metrics, and also at a visual inspection.
Journal ArticleDOI
Advances in Hyperspectral Image and Signal Processing: A Comprehensive Overview of the State of the Art
Pedram Ghamisi,Naoto Yokoya,Jun Li,Wenzhi Liao,Sicong Liu,Javier Plaza,Behnood Rasti,Antonio Plaza +7 more
TL;DR: Rigorous and innovative methodologies are required for hyperspectral image (HSI) and signal processing and have become a center of attention for researchers worldwide.
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Hyperspectral and Multispectral Data Fusion: A comparative review of the recent literature
TL;DR: Ten state-of-the-art HS-MS fusion methods are compared by assessing their fusion performance both quantitatively and visually and the generalizability and versatility of the fusion algorithms are evaluated.
References
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Book
Compressed sensing
TL;DR: It is possible to design n=O(Nlog(m)) nonadaptive measurements allowing reconstruction with accuracy comparable to that attainable with direct knowledge of the N most important coefficients, and a good approximation to those N important coefficients is extracted from the n measurements by solving a linear program-Basis Pursuit in signal processing.
Book
A wavelet tour of signal processing
TL;DR: An introduction to a Transient World and an Approximation Tour of Wavelet Packet and Local Cosine Bases.
Journal ArticleDOI
A universal image quality index
Zhou Wang,Alan C. Bovik +1 more
TL;DR: Although the new index is mathematically defined and no human visual system model is explicitly employed, experiments on various image distortion types indicate that it performs significantly better than the widely used distortion metric mean squared error.
Journal ArticleDOI
Multisensor image fusion in remote sensing: Concepts, methods and applications
Christine Pohl,J.L. van Genderen +1 more
TL;DR: This review paper describes and explains mainly pixel based image fusion of Earth observation satellite data as a contribution to multisensor integration oriented data processing.
Journal ArticleDOI
Model-order selection: a review of information criterion rules
Petre Stoica,Y. Selen +1 more
TL;DR: The parametric (or model-based) methods of signal processing often require not only the estimation of a vector of real-valued parameters but also the selection of one or several integer-valued parameter that are equally important for the specification of a data model.