Topics

Nonlocal Sparse Tensor Factorization for Semiblind Hyperspectral and Multispectral Image Fusion.

07:00 EST 28th November 2019 | BioPortfolio

Summary of "Nonlocal Sparse Tensor Factorization for Semiblind Hyperspectral and Multispectral Image Fusion."

Combining a high-spatial-resolution multispectral image (HR-MSI) with a low-spatial-resolution hyperspectral image (LR-HSI) has become a common way to enhance the spatial resolution of the HSI. The existing state-of-the-art LR-HSI and HR-MSI fusion methods are mostly based on the matrix factorization, where the matrix data representation may be hard to fully make use of the inherent structures of 3-D HSI. We propose a nonlocal sparse tensor factorization approach, called the NLSTF_SMBF, for the semiblind fusion of HSI and MSI. The proposed method decomposes the HSI into smaller full-band patches (FBPs), which, in turn, are factored as dictionaries of the three HSI modes and a sparse core tensor. This decomposition allows to solve the fusion problem as estimating a sparse core tensor and three dictionaries for each FBP. Similar FBPs are clustered together, and they are assumed to share the same dictionaries to make use of the nonlocal self-similarities of the HSI. For each group, we learn the dictionaries from the observed HR-MSI and LR-HSI. The corresponding sparse core tensor of each FBP is computed via tensor sparse coding. Two distinctive features of NLSTF_SMBF are that: 1) it is blind with respect to the point spread function (PSF) of the hyperspectral sensor and 2) it copes with spatially variant PSFs. The experimental results provide the evidence of the advantages of the NLSTF_SMBF method over the existing state-of-the-art methods, namely, in semiblind scenarios.

Affiliation

Journal Details

This article was published in the following journal.

Name: IEEE transactions on cybernetics
ISSN: 2168-2275
Pages:

Links

DeepDyve research library

PubMed Articles [3155 Associated PubMed Articles listed on BioPortfolio]

Hyperspectral Image Super-resolution via Subspace-Based Low Tensor Multi-Rank Regularization.

Recently, combining a low spatial resolution hyperspectral image (LR-HSI) with a high spatial resolution multispectral image (HR-MSI) into an HR-HSI has become a popular scheme to enhance the spatial ...

Bayesian Low-Tubal-Rank Robust Tensor Factorization with Multi-Rank Determination.

Robust tensor factorization is a fundamental problem in machine learning and computer vision, which aims at recovering tensors corrupted with outliers as a sum of the low-rank and sparse components. H...

Hyperspectral Image Restoration Using Weighted Group Sparsity-Regularized Low-Rank Tensor Decomposition.

Mixed noise (such as Gaussian, impulse, stripe, and deadline noises) contamination is a common phenomenon in hyperspectral imagery (HSI), greatly degrading visual quality and affecting subsequent proc...

Exploiting Block-sparsity for Hyperspectral Kronecker Compressive Sensing: a Tensor-based Bayesian Method.

Bayesian methods are attracting increasing attention in the field of compressive sensing (CS), as they are applicable to recover signals from random measurements. However, these methods have limited u...

Hyperspectral Pansharpening With Deep Priors.

Hyperspectral (HS) image can describe subtle differences in the spectral signatures of materials, but it has low spatial resolution limited by the existing technical and budget constraints. In this pa...

Clinical Trials [1340 Associated Clinical Trials listed on BioPortfolio]

Hyperspectral Endoscopy Imaging for the Early Detection of Precancerous Lesions in Average Risk Patients

This trial studies whether hyperspectral endoscopy improves visualization of abnormal tissue in average risk patients during standard-of-care colonoscopies. Hyperspectral endoscopy is an e...

Intraoperative Hyperspectral Imaging in Gastrointestinal Anastomoses

In this study, gastrointestinal anastomoses are examined with a hyperspectral camera.

Feasibility of Multi-Spectral Endoscopic Imaging for Detection of Early Neoplasia in Barrett's Oesophagus

Multispectral imaging represents an exciting new field of investigation in endoscopic research. Multispectral imaging uses a specialised camera to detect multiple colours, allowing us to b...

Enhancing the Lucentis (Ranibizumab) Management of Choroidal Neovascular Membranes With Hyperspectral Imaging

Clinical trial investigating the role of hyperspectral imaging in the management of patients undergoing standard clinical treatment for naive neovascular choroidal membranes in age-related...

Hyperspectral Imaging for Neoplasm Early Stage Detection

Background Information With the advance in cancer biology, we realize that malignant neoplasm is related with different biological patterns in metabolome and microbiota. Because of the pro...

Medical and Biotech [MESH] Definitions

A method of delineating blood vessels by subtracting a tissue background image from an image of tissue plus intravascular contrast material that attenuates the X-ray photons. The background image is determined from a digitized image taken a few moments before injection of the contrast material. The resulting angiogram is a high-contrast image of the vessel. This subtraction technique allows extraction of a high-intensity signal from the superimposed background information. The image is thus the result of the differential absorption of X-rays by different tissues.

The production of an image obtained by cameras that detect the radioactive emissions of an injected radionuclide as it has distributed differentially throughout tissues in the body. The image obtained from a moving detector is called a scan, while the image obtained from a stationary camera device is called a scintiphotograph.

A visual image which is recalled in accurate detail. It is a sort of projection of an image on a mental screen.

X-ray image-detecting devices that make a focused image of body structures lying in a predetermined plane from which more complex images are computed.

Improvement in the quality of an x-ray image by use of an intensifying screen, tube, or filter and by optimum exposure techniques. Digital processing methods are often employed.

Quick Search


DeepDyve research library

Relevant Topic

Antiretroviral therapy
Standard antiretroviral therapy (ART) consists of the combination of at least three antiretroviral (ARV) drugs to maximally suppress the HIV virus and stop the progression of HIV disease. Huge reductions have been seen in rates of death and suffering whe...


Searches Linking to this Article