Implementation of Sparsity-Based Unsupervised Unmixing of Hyperspectral Imaging Data using Coiflet
نویسندگان
چکیده
منابع مشابه
Sparsity-Based Unsupervised Unmixing of Hyperspectral Imaging Data Using Basis Pursuit
Abstract—Mixing in the hyperspectral imaging occurs due to the low spatial resolutions of the used cameras. The existing pure materials “endmembers” in the scene share the spectra pixels with different amounts called “abundances”. Unmixing of the data cube is an important task to know the present endmembers in the cube for the analysis of these images. Unsupervised unmixing is done with no info...
متن کاملDistributed Unmixing of Hyperspectral Data With Sparsity Constraint
Spectral unmixing (SU) is a data processing problem in hyperspectral remote sensing. The significant challenge in the SU problem is how to identify endmembers and their weights, accurately. For estimation of signature and fractional abundance matrices in a blind problem, nonnegative matrix factorization (NMF) and its developments are used widely in the SU problem. One of the constraints which w...
متن کاملUnmixing Hyperspectral Data
In hyperspectral imagery one pixel typically consists of a mixture of the re ectance spectra of several materials, where the mixture coe cients correspond to the abundances of the constituting materials. We assume linear combinations of re ectance spectra with some additive normal sensor noise and derive a probabilistic MAP framework for analyzing hyperspectral data. As the material reectance c...
متن کاملEstimating the Number of Endmembers to Use in Spectral Unmixing of Hyperspectral Data with Collaborative Sparsity
Spectral Umixing (SU) in hyperspectral remote sensing aims at recovering the signatures of the pure materials in the scene (endmembers) and their abundances in each pixel of the image. The usual SU chain does not take spectral variability (SV) into account, and relies on the estimation of the Intrinsic Dimensionality (ID) of the data, related to the number of endmembers (NOE) to use. However, t...
متن کاملSparsity Constrained Graph Regularized NMF for Spectral Unmixing of Hyperspectral Data
Hyperspectral images contain mixed pixels due to low spatial resolution of hyperspectral sensors. Mixed pixels are pixels containing more than one distinct material called endmembers. The presence percentages of endmembers in mixed pixels are called abundance fractions. Spectral unmixing problem refers to decomposing these pixels into a set of endmembers and abundance fractions. Due to nonnegat...
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ژورنال
عنوان ژورنال: The International Conference on Electrical Engineering
سال: 2018
ISSN: 2636-4441
DOI: 10.21608/iceeng.2018.30150