Data-driven approach to aesthetic enhancement

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

Research output: Contribution to journalConference articlepeer-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 languageEnglish
JournalIS and T International Symposium on Electronic Imaging Science and Technology
DOIs
Publication statusPublished - 2016
EventImage Processing: Machine Vision Applications IX 2016 - San Francisco, United States
Duration: 2016 Feb 142016 Feb 18

Bibliographical note

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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