Sparsity based reflection removal using external patch search

Reflection removal aims at separating the mixture of the desired background scenes and the undesired reflections, when the photos are taken through the glass. It has both aesthetic and practical applications which can largely improve the performance of many multimedia tasks. Existing reflection remo...

Full description

Saved in:
Bibliographic Details
Main Authors: WAN, Renjie, SHI, Boxin, TAN, Ah-hwee, KOT, Alex C.
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 2017
Subjects:
Online Access:https://ink.library.smu.edu.sg/sis_research/5480
https://ink.library.smu.edu.sg/context/sis_research/article/6483/viewcontent/Sparsity_based_reflection_removal_using_external_patch_search.pdf
Tags: Add Tag
No Tags, Be the first to tag this record!
Institution: Singapore Management University
Language: English
id sg-smu-ink.sis_research-6483
record_format dspace
spelling sg-smu-ink.sis_research-64832020-12-24T02:48:10Z Sparsity based reflection removal using external patch search WAN, Renjie SHI, Boxin TAN, Ah-hwee KOT, Alex C. Reflection removal aims at separating the mixture of the desired background scenes and the undesired reflections, when the photos are taken through the glass. It has both aesthetic and practical applications which can largely improve the performance of many multimedia tasks. Existing reflection removal approaches heavily rely on scene priors such as separable sparse gradients brought by different levels of blur, and they easily fail when such priors are not observed in many real scenes. Sparse representation models and nonlocal image priors have shown their effectiveness in image restoration with self similarity. In this work, we propose a reflection removal method benefited from the sparsity and nonlocal image prior as a unified optimization framework. We leverage the retrieved image patch from an external database to overcome the limited prior information in the input mixture image and self similarity search. The experimental results show that our proposed model performs better than the existing stateof-the-art reflection removal method for both objective and subjective image qualities. 2017-07-01T07:00:00Z text application/pdf https://ink.library.smu.edu.sg/sis_research/5480 info:doi/10.1109/ICME.2017.8019527 https://ink.library.smu.edu.sg/context/sis_research/article/6483/viewcontent/Sparsity_based_reflection_removal_using_external_patch_search.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University Reflection removal image retrieval external dataset sparse representation Databases and Information Systems Graphics and Human Computer Interfaces
institution Singapore Management University
building SMU Libraries
continent Asia
country Singapore
Singapore
content_provider SMU Libraries
collection InK@SMU
language English
topic Reflection removal
image retrieval
external dataset
sparse representation
Databases and Information Systems
Graphics and Human Computer Interfaces
spellingShingle Reflection removal
image retrieval
external dataset
sparse representation
Databases and Information Systems
Graphics and Human Computer Interfaces
WAN, Renjie
SHI, Boxin
TAN, Ah-hwee
KOT, Alex C.
Sparsity based reflection removal using external patch search
description Reflection removal aims at separating the mixture of the desired background scenes and the undesired reflections, when the photos are taken through the glass. It has both aesthetic and practical applications which can largely improve the performance of many multimedia tasks. Existing reflection removal approaches heavily rely on scene priors such as separable sparse gradients brought by different levels of blur, and they easily fail when such priors are not observed in many real scenes. Sparse representation models and nonlocal image priors have shown their effectiveness in image restoration with self similarity. In this work, we propose a reflection removal method benefited from the sparsity and nonlocal image prior as a unified optimization framework. We leverage the retrieved image patch from an external database to overcome the limited prior information in the input mixture image and self similarity search. The experimental results show that our proposed model performs better than the existing stateof-the-art reflection removal method for both objective and subjective image qualities.
format text
author WAN, Renjie
SHI, Boxin
TAN, Ah-hwee
KOT, Alex C.
author_facet WAN, Renjie
SHI, Boxin
TAN, Ah-hwee
KOT, Alex C.
author_sort WAN, Renjie
title Sparsity based reflection removal using external patch search
title_short Sparsity based reflection removal using external patch search
title_full Sparsity based reflection removal using external patch search
title_fullStr Sparsity based reflection removal using external patch search
title_full_unstemmed Sparsity based reflection removal using external patch search
title_sort sparsity based reflection removal using external patch search
publisher Institutional Knowledge at Singapore Management University
publishDate 2017
url https://ink.library.smu.edu.sg/sis_research/5480
https://ink.library.smu.edu.sg/context/sis_research/article/6483/viewcontent/Sparsity_based_reflection_removal_using_external_patch_search.pdf
_version_ 1770575474133565440