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Single image deblurring with or without face prior and its applications

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TitleInfo
Title
Single image deblurring with or without face prior and its applications
Name (type = personal)
NamePart (type = family)
Zhong
NamePart (type = given)
Lin
NamePart (type = date)
1985-
DisplayForm
Lin Zhong
Role
RoleTerm (authority = RULIB)
author
Name (type = personal)
NamePart (type = family)
Metaxas
NamePart (type = given)
Dimitris N.
DisplayForm
Dimitris N. Metaxas
Affiliation
Advisory Committee
Role
RoleTerm (authority = RULIB)
chair
Name (type = personal)
NamePart (type = family)
Elgammal
NamePart (type = given)
Ahmed
DisplayForm
Ahmed Elgammal
Affiliation
Advisory Committee
Role
RoleTerm (authority = RULIB)
internal member
Name (type = personal)
NamePart (type = family)
Bekris
NamePart (type = given)
Kostas
DisplayForm
Kostas Bekris
Affiliation
Advisory Committee
Role
RoleTerm (authority = RULIB)
internal member
Name (type = personal)
NamePart (type = family)
Samaras
NamePart (type = given)
Dimitris
DisplayForm
Dimitris Samaras
Affiliation
Advisory Committee
Role
RoleTerm (authority = RULIB)
outside member
Name (type = corporate)
NamePart
Rutgers University
Role
RoleTerm (authority = RULIB)
degree grantor
Name (type = corporate)
NamePart
Graduate School - New Brunswick
Role
RoleTerm (authority = RULIB)
school
TypeOfResource
Text
Genre (authority = marcgt)
theses
OriginInfo
DateCreated (qualifier = exact)
2015
DateOther (qualifier = exact); (type = degree)
2015-05
CopyrightDate (encoding = w3cdtf); (qualifier = exact)
2015
Place
PlaceTerm (type = code)
xx
Language
LanguageTerm (authority = ISO639-2b); (type = code)
eng
Abstract (type = abstract)
The motion blur is one of the most difficult challenges in photography, which is generated from the relative motion between the sensor and the scene during exposure time. These blur artifacts degrade the visual experience, and the performance of various applications, such as, object detection, facial analysis. Therefore, it is significant to remove the blur and restore sharp and clean images. Our work focuses on the general single image deblurring, and face image deblurring with face prior. State-of-the-art single image deblurring techniques are sensitive to image noise. Even a small amount of noise, which is inevitable in low-light conditions, can degrade the quality of blur kernel estimation dramatically. We propose a new method for handling noise in blind image deconvolution based on new theoretical and practical insights. Based on the observations on directional filter, our method applies a series of directional filters at different orientations to the input image, and estimates an accurate Radon transform of the blur kernel from each filtered image. Finally, we reconstruct the blur kernel using inverse Radon transform. Experimental results on synthetic and real data show that our algorithm achieves higher quality results than previous approaches on blurry and noisy images. The human face is one of the most essential focuses in numerous applications. Although significant progress has been made in the image deblurring area, few of them can obtain promising results on blurry face images. Many state-of-the-art single image deblurring approaches estimate the blur kernel based on analyzing the edge profiles of the input image. However, the detection of strong edges is very difficult on human faces, since the human faces do not contain as much texture as natural images. We propose to utilize the global face structure information to help with the strong or salient edge detection. Our method outperforms the existing methods in extensive evaluations on synthetic and real face images. Facial expression is a significant application on sharp and restored face images. To improve the general facial expression recognition performance, we present a new idea to analyze facial expression by exploring the common and specific information among different expressions.
Subject (authority = RUETD)
Topic
Computer Science
Subject (authority = ETD-LCSH)
Topic
Image processing--Digital techniques
Subject (authority = ETD-LCSH)
Topic
Human face recognition (Computer science)
RelatedItem (type = host)
TitleInfo
Title
Rutgers University Electronic Theses and Dissertations
Identifier (type = RULIB)
ETD
Identifier
ETD_6194
PhysicalDescription
Form (authority = gmd)
electronic resource
InternetMediaType
application/pdf
InternetMediaType
text/xml
Extent
1 online resource (xvi, 75 p. : ill.)
Note (type = degree)
Ph.D.
Note (type = bibliography)
Includes bibliographical references
Note (type = statement of responsibility)
by Lin Zhong
RelatedItem (type = host)
TitleInfo
Title
Graduate School - New Brunswick Electronic Theses and Dissertations
Identifier (type = local)
rucore19991600001
Location
PhysicalLocation (authority = marcorg); (displayLabel = Rutgers, The State University of New Jersey)
NjNbRU
Identifier (type = doi)
doi:10.7282/T3HQ41S7
Genre (authority = ExL-Esploro)
ETD doctoral
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Rights

RightsDeclaration (ID = rulibRdec0006)
The author owns the copyright to this work.
RightsHolder (type = personal)
Name
FamilyName
Zhong
GivenName
Lin
Role
Copyright Holder
RightsEvent
Type
Permission or license
DateTime (encoding = w3cdtf); (qualifier = exact); (point = start)
2015-02-25 15:02:18
AssociatedEntity
Name
LIN ZHONG
Role
Copyright holder
Affiliation
Rutgers University. Graduate School - New Brunswick
AssociatedObject
Type
License
Name
Author Agreement License
Detail
I hereby grant to the Rutgers University Libraries and to my school the non-exclusive right to archive, reproduce and distribute my thesis or dissertation, in whole or in part, and/or my abstract, in whole or in part, in and from an electronic format, subject to the release date subsequently stipulated in this submittal form and approved by my school. I represent and stipulate that the thesis or dissertation and its abstract are my original work, that they do not infringe or violate any rights of others, and that I make these grants as the sole owner of the rights to my thesis or dissertation and its abstract. I represent that I have obtained written permissions, when necessary, from the owner(s) of each third party copyrighted matter to be included in my thesis or dissertation and will supply copies of such upon request by my school. I acknowledge that RU ETD and my school will not distribute my thesis or dissertation or its abstract if, in their reasonable judgment, they believe all such rights have not been secured. I acknowledge that I retain ownership rights to the copyright of my work. I also retain the right to use all or part of this thesis or dissertation in future works, such as articles or books.
Copyright
Status
Copyright protected
Availability
Status
Open
Reason
Permission or license
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Technical

RULTechMD (ID = TECHNICAL1)
ContentModel
ETD
OperatingSystem (VERSION = 5.1)
windows xp
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