Cargando…
Mathematical Model and Synthetic Data Generation for Infra-Red Sensors
A key challenge in further improving infrared (IR) sensor capabilities is the development of efficient data pre-processing algorithms. This paper addresses this challenge by providing a mathematical model and synthetic data generation framework for an uncooled IR sensor. The developed model is capab...
Autores principales: | , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9741151/ https://www.ncbi.nlm.nih.gov/pubmed/36502160 http://dx.doi.org/10.3390/s22239458 |
_version_ | 1784848246726721536 |
---|---|
author | Leja, Laura Purlans, Vitālijs Novickis, Rihards Cvetkovs, Andrejs Ozols, Kaspars |
author_facet | Leja, Laura Purlans, Vitālijs Novickis, Rihards Cvetkovs, Andrejs Ozols, Kaspars |
author_sort | Leja, Laura |
collection | PubMed |
description | A key challenge in further improving infrared (IR) sensor capabilities is the development of efficient data pre-processing algorithms. This paper addresses this challenge by providing a mathematical model and synthetic data generation framework for an uncooled IR sensor. The developed model is capable of generating synthetic data for the design of data pre-processing algorithms of uncooled IR sensors. The mathematical model accounts for the physical characteristics of the focal plane array, bolometer readout, optics and the environment. The framework permits the sensor simulation with a range of sensor configurations, pixel defectiveness, non-uniformity and noise parameters. |
format | Online Article Text |
id | pubmed-9741151 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-97411512022-12-11 Mathematical Model and Synthetic Data Generation for Infra-Red Sensors Leja, Laura Purlans, Vitālijs Novickis, Rihards Cvetkovs, Andrejs Ozols, Kaspars Sensors (Basel) Article A key challenge in further improving infrared (IR) sensor capabilities is the development of efficient data pre-processing algorithms. This paper addresses this challenge by providing a mathematical model and synthetic data generation framework for an uncooled IR sensor. The developed model is capable of generating synthetic data for the design of data pre-processing algorithms of uncooled IR sensors. The mathematical model accounts for the physical characteristics of the focal plane array, bolometer readout, optics and the environment. The framework permits the sensor simulation with a range of sensor configurations, pixel defectiveness, non-uniformity and noise parameters. MDPI 2022-12-03 /pmc/articles/PMC9741151/ /pubmed/36502160 http://dx.doi.org/10.3390/s22239458 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Leja, Laura Purlans, Vitālijs Novickis, Rihards Cvetkovs, Andrejs Ozols, Kaspars Mathematical Model and Synthetic Data Generation for Infra-Red Sensors |
title | Mathematical Model and Synthetic Data Generation for Infra-Red Sensors |
title_full | Mathematical Model and Synthetic Data Generation for Infra-Red Sensors |
title_fullStr | Mathematical Model and Synthetic Data Generation for Infra-Red Sensors |
title_full_unstemmed | Mathematical Model and Synthetic Data Generation for Infra-Red Sensors |
title_short | Mathematical Model and Synthetic Data Generation for Infra-Red Sensors |
title_sort | mathematical model and synthetic data generation for infra-red sensors |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9741151/ https://www.ncbi.nlm.nih.gov/pubmed/36502160 http://dx.doi.org/10.3390/s22239458 |
work_keys_str_mv | AT lejalaura mathematicalmodelandsyntheticdatagenerationforinfraredsensors AT purlansvitalijs mathematicalmodelandsyntheticdatagenerationforinfraredsensors AT novickisrihards mathematicalmodelandsyntheticdatagenerationforinfraredsensors AT cvetkovsandrejs mathematicalmodelandsyntheticdatagenerationforinfraredsensors AT ozolskaspars mathematicalmodelandsyntheticdatagenerationforinfraredsensors |