Data-driven approach to aesthetic enhancement

Jihye Choi; Sungjoon Koh; Jongwoo Kwack; Yonghun Kwon; Hyunjung Shim

doi:10.2352/ISSN.2470-1173.2016.14.IPMVA-374

Data-driven approach to aesthetic enhancement

Jihye Choi, Sungjoon Koh, Jongwoo Kwack, Yonghun Kwon, Hyunjung Shim

School of Integrated Technology

Research output: Contribution to journal › Conference article › peer-review

1 Citation (Scopus)

Abstract

Traditional image enhancement techniques revise the distribution of pixels or local structure and achieve the impressive performance in image denoising, contrast enhancement and color adjustment. However, they are not effective to improve the overall aesthetic image quality because it may involve contextual modifications, including the removal of disturbing objects, inclusion of appealing visual elements or relocation of the target object. In this paper, we propose a new aesthetic enhancement technique that edits the structural image element guided by a large collection of good exemplars. More specifically, we remove/insert image elements and resize/relocate objects based on good exemplars. Additionally, we remove undesirable regions determined by user interaction and fill these holes seamlessly guided by the exemplars. Based on the experimental evaluation on the database of two landmarks, we observe the considerable improvement in aesthetic quality.

Original language	English
Journal	IS and T International Symposium on Electronic Imaging Science and Technology
DOIs	https://doi.org/10.2352/ISSN.2470-1173.2016.14.IPMVA-374
Publication status	Published - 2016
Event	Image Processing: Machine Vision Applications IX 2016 - San Francisco, United States Duration: 2016 Feb 14 → 2016 Feb 18

Bibliographical note

Funding Information:
This research was supported by the MSIP(Ministry of Science, ICT and Future Planning), Korea, under the IT Consilience Creative Program (IITP-2015-R0346-15-1008) supervised by the IITP(Institute for Information & Communications Technology Promotion) and also the Basic Science Research Program through the National Research Foundation of Korea(NRF) funded by the Ministry of Science, ICT and Future Planning (NRF-2013R1A1A1062644).

Publisher Copyright:
© 2016 Society for Imaging Science and Technology.

All Science Journal Classification (ASJC) codes

Computer Graphics and Computer-Aided Design
Computer Science Applications
Human-Computer Interaction
Software
Electrical and Electronic Engineering
Atomic and Molecular Physics, and Optics

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10.2352/ISSN.2470-1173.2016.14.IPMVA-374

Cite this

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title = "Data-driven approach to aesthetic enhancement",

abstract = "Traditional image enhancement techniques revise the distribution of pixels or local structure and achieve the impressive performance in image denoising, contrast enhancement and color adjustment. However, they are not effective to improve the overall aesthetic image quality because it may involve contextual modifications, including the removal of disturbing objects, inclusion of appealing visual elements or relocation of the target object. In this paper, we propose a new aesthetic enhancement technique that edits the structural image element guided by a large collection of good exemplars. More specifically, we remove/insert image elements and resize/relocate objects based on good exemplars. Additionally, we remove undesirable regions determined by user interaction and fill these holes seamlessly guided by the exemplars. Based on the experimental evaluation on the database of two landmarks, we observe the considerable improvement in aesthetic quality.",

author = "Jihye Choi and Sungjoon Koh and Jongwoo Kwack and Yonghun Kwon and Hyunjung Shim",

note = "Funding Information: This research was supported by the MSIP(Ministry of Science, ICT and Future Planning), Korea, under the IT Consilience Creative Program (IITP-2015-R0346-15-1008) supervised by the IITP(Institute for Information & Communications Technology Promotion) and also the Basic Science Research Program through the National Research Foundation of Korea(NRF) funded by the Ministry of Science, ICT and Future Planning (NRF-2013R1A1A1062644). Publisher Copyright: {\textcopyright} 2016 Society for Imaging Science and Technology.; Image Processing: Machine Vision Applications IX 2016 ; Conference date: 14-02-2016 Through 18-02-2016",

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doi = "10.2352/ISSN.2470-1173.2016.14.IPMVA-374",

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AU - Choi, Jihye

AU - Koh, Sungjoon

AU - Kwack, Jongwoo

AU - Kwon, Yonghun

AU - Shim, Hyunjung

N1 - Funding Information: This research was supported by the MSIP(Ministry of Science, ICT and Future Planning), Korea, under the IT Consilience Creative Program (IITP-2015-R0346-15-1008) supervised by the IITP(Institute for Information & Communications Technology Promotion) and also the Basic Science Research Program through the National Research Foundation of Korea(NRF) funded by the Ministry of Science, ICT and Future Planning (NRF-2013R1A1A1062644). Publisher Copyright: © 2016 Society for Imaging Science and Technology.

PY - 2016

Y1 - 2016

N2 - Traditional image enhancement techniques revise the distribution of pixels or local structure and achieve the impressive performance in image denoising, contrast enhancement and color adjustment. However, they are not effective to improve the overall aesthetic image quality because it may involve contextual modifications, including the removal of disturbing objects, inclusion of appealing visual elements or relocation of the target object. In this paper, we propose a new aesthetic enhancement technique that edits the structural image element guided by a large collection of good exemplars. More specifically, we remove/insert image elements and resize/relocate objects based on good exemplars. Additionally, we remove undesirable regions determined by user interaction and fill these holes seamlessly guided by the exemplars. Based on the experimental evaluation on the database of two landmarks, we observe the considerable improvement in aesthetic quality.

AB - Traditional image enhancement techniques revise the distribution of pixels or local structure and achieve the impressive performance in image denoising, contrast enhancement and color adjustment. However, they are not effective to improve the overall aesthetic image quality because it may involve contextual modifications, including the removal of disturbing objects, inclusion of appealing visual elements or relocation of the target object. In this paper, we propose a new aesthetic enhancement technique that edits the structural image element guided by a large collection of good exemplars. More specifically, we remove/insert image elements and resize/relocate objects based on good exemplars. Additionally, we remove undesirable regions determined by user interaction and fill these holes seamlessly guided by the exemplars. Based on the experimental evaluation on the database of two landmarks, we observe the considerable improvement in aesthetic quality.

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SN - 2470-1173

JO - IS and T International Symposium on Electronic Imaging Science and Technology

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T2 - Image Processing: Machine Vision Applications IX 2016

Y2 - 14 February 2016 through 18 February 2016

ER -

Data-driven approach to aesthetic enhancement

Abstract

Bibliographical note

All Science Journal Classification (ASJC) codes

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