Advances in image restoration: from theory to practice

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985556%3A_____%2F15%3A00444197" target="_blank" >RIV/67985556:_____/15:00444197 - isvavai.cz</a>

Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Advances in image restoration: from theory to practice

Popis výsledku v původním jazyce

We rely on images with ever growing emphasis. Our perception of the world is however limited by imperfect measuring conditions and devices used to acquire images. By image restoration, we understand mathematical procedures removing degradation from images. Two prominent topics of image restoration that has evolved considerably in the last 10 years are blind deconvolution and superresolution. Deconvolution by itself is an ill-posed inverse problem and one of the fundamental topics of image processing. The blind case, when the blur kernel is also unknown, is even more challenging and requires special optimization approaches to converge to the correct solution. Superresolution extends blind deconvolution by recovering lost spatial resolution of images. Inthis talk we will cover the recent advances in both topics that pave the way from theory to practice. Various real acquisition scenarios will be discussed together with proposed solutions for both blind deconvolution and superresolution

Název v anglickém jazyce

Advances in image restoration: from theory to practice

Popis výsledku anglicky

We rely on images with ever growing emphasis. Our perception of the world is however limited by imperfect measuring conditions and devices used to acquire images. By image restoration, we understand mathematical procedures removing degradation from images. Two prominent topics of image restoration that has evolved considerably in the last 10 years are blind deconvolution and superresolution. Deconvolution by itself is an ill-posed inverse problem and one of the fundamental topics of image processing. The blind case, when the blur kernel is also unknown, is even more challenging and requires special optimization approaches to converge to the correct solution. Superresolution extends blind deconvolution by recovering lost spatial resolution of images. Inthis talk we will cover the recent advances in both topics that pave the way from theory to practice. Various real acquisition scenarios will be discussed together with proposed solutions for both blind deconvolution and superresolution

Druh

O - Ostatní výsledky

CEP obor

JD - Využití počítačů, robotika a její aplikace

OECD FORD obor

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Projekt

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Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2015

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů