Reproducibility of Pansharpening Methods and Quality Indexes versus Data Formats

In this work, we investigate whether the performance of pansharpening methods depends on their input data format; in the case of spectral radiance, either in its original floating-point format or in an integer-packed fixed-point format. It is theoretically proven and experimentally demonstrated that...

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Autores principales:	Alberto Arienzo, Bruno Aiazzi, Luciano Alparone, Andrea Garzelli
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	data formats multispectral images pansharpening remote sensing reproducibility statistical quality indexes Science Q
Acceso en línea:	https://doaj.org/article/08d1d037dfe941a3b8bf05034954e8dd
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spelling	oai:doaj.org-article:08d1d037dfe941a3b8bf05034954e8dd2021-11-11T18:55:32ZReproducibility of Pansharpening Methods and Quality Indexes versus Data Formats10.3390/rs132143992072-4292https://doaj.org/article/08d1d037dfe941a3b8bf05034954e8dd2021-10-01T00:00:00Zhttps://www.mdpi.com/2072-4292/13/21/4399https://doaj.org/toc/2072-4292In this work, we investigate whether the performance of pansharpening methods depends on their input data format; in the case of spectral radiance, either in its original floating-point format or in an integer-packed fixed-point format. It is theoretically proven and experimentally demonstrated that methods based on multiresolution analysis are unaffected by the data format. Conversely, the format is crucial for methods based on component substitution, unless the intensity component is calculated by means of a multivariate linear regression between the upsampled bands and the lowpass-filtered Pan. Another concern related to data formats is whether quality measurements, carried out by means of normalized indexes depend on the format of the data on which they are calculated. We will focus on some of the most widely used with-reference indexes to provide a novel insight into their behaviors. Both theoretical analyses and computer simulations, carried out on GeoEye-1 and WorldView-2 datasets with the products of nine pansharpening methods, show that their performance does not depend on the data format for purely radiometric indexes, while it significantly depends on the data format, either floating-point or fixed-point, for a purely spectral index, like the spectral angle mapper. The dependence on the data format is weak for indexes that balance the spectral and radiometric similarity, like the family of indexes, Q2<sup><i>n</i></sup>, based on hypercomplex algebra.Alberto ArienzoBruno AiazziLuciano AlparoneAndrea GarzelliMDPI AGarticledata formatsmultispectral imagespansharpeningremote sensingreproducibilitystatistical quality indexesScienceQENRemote Sensing, Vol 13, Iss 4399, p 4399 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	data formats multispectral images pansharpening remote sensing reproducibility statistical quality indexes Science Q
spellingShingle	data formats multispectral images pansharpening remote sensing reproducibility statistical quality indexes Science Q Alberto Arienzo Bruno Aiazzi Luciano Alparone Andrea Garzelli Reproducibility of Pansharpening Methods and Quality Indexes versus Data Formats
description	In this work, we investigate whether the performance of pansharpening methods depends on their input data format; in the case of spectral radiance, either in its original floating-point format or in an integer-packed fixed-point format. It is theoretically proven and experimentally demonstrated that methods based on multiresolution analysis are unaffected by the data format. Conversely, the format is crucial for methods based on component substitution, unless the intensity component is calculated by means of a multivariate linear regression between the upsampled bands and the lowpass-filtered Pan. Another concern related to data formats is whether quality measurements, carried out by means of normalized indexes depend on the format of the data on which they are calculated. We will focus on some of the most widely used with-reference indexes to provide a novel insight into their behaviors. Both theoretical analyses and computer simulations, carried out on GeoEye-1 and WorldView-2 datasets with the products of nine pansharpening methods, show that their performance does not depend on the data format for purely radiometric indexes, while it significantly depends on the data format, either floating-point or fixed-point, for a purely spectral index, like the spectral angle mapper. The dependence on the data format is weak for indexes that balance the spectral and radiometric similarity, like the family of indexes, Q2<sup><i>n</i></sup>, based on hypercomplex algebra.
format	article
author	Alberto Arienzo Bruno Aiazzi Luciano Alparone Andrea Garzelli
author_facet	Alberto Arienzo Bruno Aiazzi Luciano Alparone Andrea Garzelli
author_sort	Alberto Arienzo
title	Reproducibility of Pansharpening Methods and Quality Indexes versus Data Formats
title_short	Reproducibility of Pansharpening Methods and Quality Indexes versus Data Formats
title_full	Reproducibility of Pansharpening Methods and Quality Indexes versus Data Formats
title_fullStr	Reproducibility of Pansharpening Methods and Quality Indexes versus Data Formats
title_full_unstemmed	Reproducibility of Pansharpening Methods and Quality Indexes versus Data Formats
title_sort	reproducibility of pansharpening methods and quality indexes versus data formats
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/08d1d037dfe941a3b8bf05034954e8dd
work_keys_str_mv	AT albertoarienzo reproducibilityofpansharpeningmethodsandqualityindexesversusdataformats AT brunoaiazzi reproducibilityofpansharpeningmethodsandqualityindexesversusdataformats AT lucianoalparone reproducibilityofpansharpeningmethodsandqualityindexesversusdataformats AT andreagarzelli reproducibilityofpansharpeningmethodsandqualityindexesversusdataformats
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Reproducibility of Pansharpening Methods and Quality Indexes versus Data Formats

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