A Smooth Non-Iterative Local Polynomial (SNILP) Model of Image Vignetting

Image vignetting is one of the major radiometric errors, which occurs in lens-camera systems. In many applications, vignetting is an undesirable phenomenon; therefore, when it is impossible to fully prevent its occurrence, it is necessary to use computational methods for its correction in the acquir...

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Autores principales:	Artur Bal, Henryk Palus
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	image vignetting lens shading vignetting correction flat-field correction vignetting modeling approximation function Chemical technology TP1-1185
Acceso en línea:	https://doaj.org/article/2024ba7b35734d4188065bc80113d920
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spelling	oai:doaj.org-article:2024ba7b35734d4188065bc80113d9202021-11-11T19:06:07ZA Smooth Non-Iterative Local Polynomial (SNILP) Model of Image Vignetting10.3390/s212170861424-8220https://doaj.org/article/2024ba7b35734d4188065bc80113d9202021-10-01T00:00:00Zhttps://www.mdpi.com/1424-8220/21/21/7086https://doaj.org/toc/1424-8220Image vignetting is one of the major radiometric errors, which occurs in lens-camera systems. In many applications, vignetting is an undesirable phenomenon; therefore, when it is impossible to fully prevent its occurrence, it is necessary to use computational methods for its correction in the acquired image. In the most frequently used approach to the vignetting correction, i.e., the flat-field correction, the usage of appropriate vignetting models plays a crucial role. In the article, the new model of vignetting, i.e., Smooth Non-Iterative Local Polynomial (SNILP) model, is proposed. The SNILP model was compared with the models known from the literature, e.g., the polynomial 2D and radial polynomial models, in a series of numerical tests and in the real-data experiment. The obtained results prove that the SNILP model usually gives better vignetting correction results than the other aforementioned tested models. For images larger than UXGA format (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>1600</mn><mo>×</mo><mn>1200</mn></mrow></semantics></math></inline-formula>), the proposed model is also faster than other tested models. Moreover, among the tested models, the SNILP model requires the least hardware resources for its application. This means that the SNILP model is suitable for its usage in devices with limited computing power.Artur BalHenryk PalusMDPI AGarticleimage vignettinglens shadingvignetting correctionflat-field correctionvignetting modelingapproximation functionChemical technologyTP1-1185ENSensors, Vol 21, Iss 7086, p 7086 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	image vignetting lens shading vignetting correction flat-field correction vignetting modeling approximation function Chemical technology TP1-1185
spellingShingle	image vignetting lens shading vignetting correction flat-field correction vignetting modeling approximation function Chemical technology TP1-1185 Artur Bal Henryk Palus A Smooth Non-Iterative Local Polynomial (SNILP) Model of Image Vignetting
description	Image vignetting is one of the major radiometric errors, which occurs in lens-camera systems. In many applications, vignetting is an undesirable phenomenon; therefore, when it is impossible to fully prevent its occurrence, it is necessary to use computational methods for its correction in the acquired image. In the most frequently used approach to the vignetting correction, i.e., the flat-field correction, the usage of appropriate vignetting models plays a crucial role. In the article, the new model of vignetting, i.e., Smooth Non-Iterative Local Polynomial (SNILP) model, is proposed. The SNILP model was compared with the models known from the literature, e.g., the polynomial 2D and radial polynomial models, in a series of numerical tests and in the real-data experiment. The obtained results prove that the SNILP model usually gives better vignetting correction results than the other aforementioned tested models. For images larger than UXGA format (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>1600</mn><mo>×</mo><mn>1200</mn></mrow></semantics></math></inline-formula>), the proposed model is also faster than other tested models. Moreover, among the tested models, the SNILP model requires the least hardware resources for its application. This means that the SNILP model is suitable for its usage in devices with limited computing power.
format	article
author	Artur Bal Henryk Palus
author_facet	Artur Bal Henryk Palus
author_sort	Artur Bal
title	A Smooth Non-Iterative Local Polynomial (SNILP) Model of Image Vignetting
title_short	A Smooth Non-Iterative Local Polynomial (SNILP) Model of Image Vignetting
title_full	A Smooth Non-Iterative Local Polynomial (SNILP) Model of Image Vignetting
title_fullStr	A Smooth Non-Iterative Local Polynomial (SNILP) Model of Image Vignetting
title_full_unstemmed	A Smooth Non-Iterative Local Polynomial (SNILP) Model of Image Vignetting
title_sort	smooth non-iterative local polynomial (snilp) model of image vignetting
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/2024ba7b35734d4188065bc80113d920
work_keys_str_mv	AT arturbal asmoothnoniterativelocalpolynomialsnilpmodelofimagevignetting AT henrykpalus asmoothnoniterativelocalpolynomialsnilpmodelofimagevignetting AT arturbal smoothnoniterativelocalpolynomialsnilpmodelofimagevignetting AT henrykpalus smoothnoniterativelocalpolynomialsnilpmodelofimagevignetting
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A Smooth Non-Iterative Local Polynomial (SNILP) Model of Image Vignetting

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