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Integration of Satellite Data with High Resolution Ratio: Improvement of Spectral Quality with Preserving Spatial Details
Commonly used image fusion techniques generally produce good results for images obtained from the same sensor, with a standard ratio of spatial resolution (1:4). However, an atypical high ratio of resolution reduces the effectiveness of fusion methods resulting in a decrease in the spectral or spati...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6308569/ https://www.ncbi.nlm.nih.gov/pubmed/30551674 http://dx.doi.org/10.3390/s18124418 |
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author | Sekrecka, Aleksandra Kedzierski, Michal |
author_facet | Sekrecka, Aleksandra Kedzierski, Michal |
author_sort | Sekrecka, Aleksandra |
collection | PubMed |
description | Commonly used image fusion techniques generally produce good results for images obtained from the same sensor, with a standard ratio of spatial resolution (1:4). However, an atypical high ratio of resolution reduces the effectiveness of fusion methods resulting in a decrease in the spectral or spatial quality of the sharpened image. An important issue is the development of a method that allows for maintaining simultaneous high spatial and spectral quality. The authors propose to strengthen the pan-sharpening methods through prior modification of the panchromatic image. Local statistics of the differences between the original panchromatic image and the intensity of the multispectral image are used to detect spatial details. The Euler’s number and the distance of each pixel from the nearest pixel classified as a spatial detail determine the weight of the information collected from each integrated image. The research was carried out for several pan-sharpening methods and for data sets with different levels of spectral matching. The proposed solution allows for a greater improvement in the quality of spectral fusion, while being able to identify the same spatial details for most pan-sharpening methods and is mainly dedicated to Intensity-Hue-Saturation based methods for which the following improvements in spectral quality were achieved: about 30% for the urbanized area and about 15% for the non-urbanized area. |
format | Online Article Text |
id | pubmed-6308569 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-63085692019-01-04 Integration of Satellite Data with High Resolution Ratio: Improvement of Spectral Quality with Preserving Spatial Details Sekrecka, Aleksandra Kedzierski, Michal Sensors (Basel) Article Commonly used image fusion techniques generally produce good results for images obtained from the same sensor, with a standard ratio of spatial resolution (1:4). However, an atypical high ratio of resolution reduces the effectiveness of fusion methods resulting in a decrease in the spectral or spatial quality of the sharpened image. An important issue is the development of a method that allows for maintaining simultaneous high spatial and spectral quality. The authors propose to strengthen the pan-sharpening methods through prior modification of the panchromatic image. Local statistics of the differences between the original panchromatic image and the intensity of the multispectral image are used to detect spatial details. The Euler’s number and the distance of each pixel from the nearest pixel classified as a spatial detail determine the weight of the information collected from each integrated image. The research was carried out for several pan-sharpening methods and for data sets with different levels of spectral matching. The proposed solution allows for a greater improvement in the quality of spectral fusion, while being able to identify the same spatial details for most pan-sharpening methods and is mainly dedicated to Intensity-Hue-Saturation based methods for which the following improvements in spectral quality were achieved: about 30% for the urbanized area and about 15% for the non-urbanized area. MDPI 2018-12-13 /pmc/articles/PMC6308569/ /pubmed/30551674 http://dx.doi.org/10.3390/s18124418 Text en © 2018 by the authors. 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 (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Sekrecka, Aleksandra Kedzierski, Michal Integration of Satellite Data with High Resolution Ratio: Improvement of Spectral Quality with Preserving Spatial Details |
title | Integration of Satellite Data with High Resolution Ratio: Improvement of Spectral Quality with Preserving Spatial Details |
title_full | Integration of Satellite Data with High Resolution Ratio: Improvement of Spectral Quality with Preserving Spatial Details |
title_fullStr | Integration of Satellite Data with High Resolution Ratio: Improvement of Spectral Quality with Preserving Spatial Details |
title_full_unstemmed | Integration of Satellite Data with High Resolution Ratio: Improvement of Spectral Quality with Preserving Spatial Details |
title_short | Integration of Satellite Data with High Resolution Ratio: Improvement of Spectral Quality with Preserving Spatial Details |
title_sort | integration of satellite data with high resolution ratio: improvement of spectral quality with preserving spatial details |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6308569/ https://www.ncbi.nlm.nih.gov/pubmed/30551674 http://dx.doi.org/10.3390/s18124418 |
work_keys_str_mv | AT sekreckaaleksandra integrationofsatellitedatawithhighresolutionratioimprovementofspectralqualitywithpreservingspatialdetails AT kedzierskimichal integrationofsatellitedatawithhighresolutionratioimprovementofspectralqualitywithpreservingspatialdetails |