# Development of a Random Field Model for Gas Plume Detection in Multiple LWIR Images.

## Abstract

This report develops a random field model that describes gas plumes in LWIR remote sensing images. The random field model serves as a prior distribution that can be combined with LWIR data to produce a posterior that determines the probability that a gas plume exists in the scene and also maps the most probable location of any plume. The random field model is intended to work with a single pixel regression estimator--a regression model that estimates gas concentration on an individual pixel basis.

- Authors:

- Publication Date:

- Research Org.:
- Pacific Northwest National Lab. (PNNL), Richland, WA (United States)

- Sponsoring Org.:
- USDOE

- OSTI Identifier:
- 1133250

- Report Number(s):
- PNNL-17873

NN2001000

- DOE Contract Number:
- AC05-76RL01830

- Resource Type:
- Technical Report

- Country of Publication:
- United States

- Language:
- English

### Citation Formats

```
Heasler, Patrick G.
```*Development of a Random Field Model for Gas Plume Detection in Multiple LWIR Images.*. United States: N. p., 2008.
Web. doi:10.2172/1133250.

```
Heasler, Patrick G.
```*Development of a Random Field Model for Gas Plume Detection in Multiple LWIR Images.*. United States. doi:10.2172/1133250.

```
Heasler, Patrick G. Tue .
"Development of a Random Field Model for Gas Plume Detection in Multiple LWIR Images.". United States. doi:10.2172/1133250. https://www.osti.gov/servlets/purl/1133250.
```

```
@article{osti_1133250,
```

title = {Development of a Random Field Model for Gas Plume Detection in Multiple LWIR Images.},

author = {Heasler, Patrick G.},

abstractNote = {This report develops a random field model that describes gas plumes in LWIR remote sensing images. The random field model serves as a prior distribution that can be combined with LWIR data to produce a posterior that determines the probability that a gas plume exists in the scene and also maps the most probable location of any plume. The random field model is intended to work with a single pixel regression estimator--a regression model that estimates gas concentration on an individual pixel basis.},

doi = {10.2172/1133250},

journal = {},

number = ,

volume = ,

place = {United States},

year = {Tue Sep 30 00:00:00 EDT 2008},

month = {Tue Sep 30 00:00:00 EDT 2008}

}

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