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dc.contributor.advisor 좌훈승 -
dc.contributor.author Janghun Jo -
dc.date.accessioned 2020-06-22T16:03:44Z -
dc.date.available 2020-06-22T16:03:44Z -
dc.date.issued 2020 -
dc.identifier.uri http://dgist.dcollection.net/common/orgView/200000283399 en_US
dc.identifier.uri http://hdl.handle.net/20.500.11750/12021 -
dc.description image processing, deblurring, deep learning -
dc.description.statementofresponsibility prohibition -
dc.description.tableofcontents I. Introduction 1
II. Background 4
2.1. Non-blind Image Deblurring 4
2.2. Richardson-Lucy Deconvolution 5
III. Related Work 6
3.1. Non-uniform blur. 6
IV. Methods 8
4.1. Parameterizing Richardson-Lucy Deconvolution 8
4.2. Deep Richardson-Lucy Deconvolution 9
4.3. Feature Scaling 11
4.4. Non-uniform Deblurring 11
4.5. Handling Boundary Artifact 13
4.6. Training 14
4.7. Dataset 14
4.8. Implementation 15
V. Experiments 17
5.1. Uniform Deblurring 17
5.2. Non-uniform Deblurring 20
5.3. Evaluation on Poisson noise 22
VI. Conclusion 24
References 25
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dc.format.extent 41 -
dc.language eng -
dc.publisher DGIST -
dc.title Deep Richardson-Lucy Deconvolution -
dc.type Thesis -
dc.identifier.doi 10.22677/Theses.200000283399 -
dc.description.degree Master -
dc.contributor.department Information and Communication Engineering -
dc.contributor.coadvisor Sunghyun Cho -
dc.date.awarded 2020-02 -
dc.publisher.location Daegu -
dc.description.database dCollection -
dc.citation XT.IM 조72 202002 -
dc.date.accepted 2020-01-20 -
dc.contributor.alternativeDepartment 정보통신융합전공 -
dc.embargo.liftdate 2021-12-31 -
dc.contributor.affiliatedAuthor Jo, Janghun -
dc.contributor.affiliatedAuthor Cho, Sunghyun -
dc.contributor.affiliatedAuthor Chwa, Hoon Sung -
dc.contributor.alternativeName 조장훈 -
dc.contributor.alternativeName 조성현 -
dc.contributor.alternativeName Hoonsung Chwa -
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Department of Electrical Engineering and Computer Science Theses Master

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