Probabilistic Mixture Model-Based Spectral Unmixing Article Swipe
Oliver Hoidn
,
Aashwin Mishra
,
Apurva Mehta
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.3390/app14114836
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.3390/app14114836
Spectral unmixing attempts to decompose a spectral ensemble into the constituent pure spectral signatures (called endmembers) along with the proportion of each endmember. This is essential for techniques like hyperspectral imaging (HSI) used in environment monitoring, geological exploration, etc. Several spectral unmixing approaches have been proposed, many of which are connected to hyperspectral imaging. However, most extant approaches assume highly diverse collections of mixtures and extremely low-loss spectroscopic measurements. Additionally, current non-Bayesian frameworks do not incorporate the uncertainty inherent in unmixing. We propose a probabilistic inference algorithm that explicitly incorporates noise and uncertainty, enabling us to unmix endmembers in collections of mixtures with limited diversity. We use a Bayesian mixture model to jointly extract endmember spectra and mixing parameters while explicitly modeling observation noise and the resulting inference uncertainties. We obtain approximate distributions over endmember coordinates for each set of observed spectra while remaining robust to inference biases from the lack of pure observations and the presence of non-isotropic Gaussian noise. As a direct impact of our methodology, access to reliable uncertainties on the unmixing solutions would enable robust solutions to noise, as well as informed decision-making for HSI applications and other unmixing problems.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3390/app14114836
- https://www.mdpi.com/2076-3417/14/11/4836/pdf?version=1717407211
- OA Status
- gold
- Cited By
- 1
- References
- 22
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4399288837
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4399288837Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.3390/app14114836Digital Object Identifier
- Title
-
Probabilistic Mixture Model-Based Spectral UnmixingWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
-
2024Year of publication
- Publication date
-
2024-06-03Full publication date if available
- Authors
-
Oliver Hoidn, Aashwin Mishra, Apurva MehtaList of authors in order
- Landing page
-
https://doi.org/10.3390/app14114836Publisher landing page
- PDF URL
-
https://www.mdpi.com/2076-3417/14/11/4836/pdf?version=1717407211Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://www.mdpi.com/2076-3417/14/11/4836/pdf?version=1717407211Direct OA link when available
- Concepts
-
Endmember, Hyperspectral imaging, Mixture model, Probabilistic logic, Inference, Computer science, Artificial intelligence, Bayesian inference, Pattern recognition (psychology), Noise (video), Bayesian probability, Image (mathematics)Top concepts (fields/topics) attached by OpenAlex
- Cited by
-
1Total citation count in OpenAlex
- Citations by year (recent)
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2024: 1Per-year citation counts (last 5 years)
- References (count)
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22Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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