Image De-Quantization Using Plate Bending Model

Discretized image signals might have a lower dynamic range than the display. Because of this, false contours might appear when the image has the same pixel value for a larger region and the distance between pixel levels reaches the noticeable difference threshold. There have been several methods aim...

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Main Authors: David Völgyes, Anne Catrine Trægde Martinsen, Arne Stray-Pedersen, Dag Waaler, Marius Pedersen
Format: Article
Language:English
Published: MDPI AG 2018-07-01
Series:Algorithms
Subjects:
Online Access:http://www.mdpi.com/1999-4893/11/8/110
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spelling doaj-47a20e61637146169f6d473ccf9584a62020-11-24T23:58:46ZengMDPI AGAlgorithms1999-48932018-07-0111811010.3390/a11080110a11080110Image De-Quantization Using Plate Bending ModelDavid Völgyes0Anne Catrine Trægde Martinsen1Arne Stray-Pedersen2Dag Waaler3Marius Pedersen4Department of Computer Science, Norwegian University of Science and Technology, 2815 Gjøvik, NorwayDepartment of Physics, University of Oslo, 0316 Oslo, NorwayDepartment of Forensic Sciences, Oslo University Hospital, 0424 Oslo, NorwayDepartment of Health Sciences in Gjøvik, Norwegian University of Science and Technology, 2803 Gjøvik, NorwayDepartment of Computer Science, Norwegian University of Science and Technology, 2815 Gjøvik, NorwayDiscretized image signals might have a lower dynamic range than the display. Because of this, false contours might appear when the image has the same pixel value for a larger region and the distance between pixel levels reaches the noticeable difference threshold. There have been several methods aimed at approximating the high bit depth of the original signal. Our method models a region with a bended plate model, which leads to the biharmonic equation. This method addresses several new aspects: the reconstruction of non-continuous regions when foreground objects split the area into separate regions; the incorporation of confidence about pixel levels, making the model tunable; and the method gives a physics-inspired way to handle local maximal/minimal regions. The solution of the biharmonic equation yields a smooth high-order signal approximation and handles the local maxima/minima problems.http://www.mdpi.com/1999-4893/11/8/110de-quantizationfalse contour removalbit depth enhancementbiharmonic equationpartial differential equations
collection DOAJ
language English
format Article
sources DOAJ
author David Völgyes
Anne Catrine Trægde Martinsen
Arne Stray-Pedersen
Dag Waaler
Marius Pedersen
spellingShingle David Völgyes
Anne Catrine Trægde Martinsen
Arne Stray-Pedersen
Dag Waaler
Marius Pedersen
Image De-Quantization Using Plate Bending Model
Algorithms
de-quantization
false contour removal
bit depth enhancement
biharmonic equation
partial differential equations
author_facet David Völgyes
Anne Catrine Trægde Martinsen
Arne Stray-Pedersen
Dag Waaler
Marius Pedersen
author_sort David Völgyes
title Image De-Quantization Using Plate Bending Model
title_short Image De-Quantization Using Plate Bending Model
title_full Image De-Quantization Using Plate Bending Model
title_fullStr Image De-Quantization Using Plate Bending Model
title_full_unstemmed Image De-Quantization Using Plate Bending Model
title_sort image de-quantization using plate bending model
publisher MDPI AG
series Algorithms
issn 1999-4893
publishDate 2018-07-01
description Discretized image signals might have a lower dynamic range than the display. Because of this, false contours might appear when the image has the same pixel value for a larger region and the distance between pixel levels reaches the noticeable difference threshold. There have been several methods aimed at approximating the high bit depth of the original signal. Our method models a region with a bended plate model, which leads to the biharmonic equation. This method addresses several new aspects: the reconstruction of non-continuous regions when foreground objects split the area into separate regions; the incorporation of confidence about pixel levels, making the model tunable; and the method gives a physics-inspired way to handle local maximal/minimal regions. The solution of the biharmonic equation yields a smooth high-order signal approximation and handles the local maxima/minima problems.
topic de-quantization
false contour removal
bit depth enhancement
biharmonic equation
partial differential equations
url http://www.mdpi.com/1999-4893/11/8/110
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AT arnestraypedersen imagedequantizationusingplatebendingmodel
AT dagwaaler imagedequantizationusingplatebendingmodel
AT mariuspedersen imagedequantizationusingplatebendingmodel
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