Visual salience and stack extension based ghost removal for high-dynamic-range imaging

Zijie Wang, Qin Liu, Takeshi Ikenaga

研究成果: Conference contribution

1 被引用数 (Scopus)

抄録

High-dynamic-range imaging (HDRI) techniques are proposed to extend the dynamic range of captured images against sensor limitation. The key issue of multi-exposure fusion in HDRI is removing ghost artifacts caused by motion of moving objects and handheld cameras. This paper proposes a ghost-free HDRI algorithm based on visual salience and stack extension. To improve the accuracy of ghost areas detection, visual salience based bilateral motion detection is introduced to measure image differences. For exposure fusion, the proposed algorithm reduces brightness discontinuity and enhances details by stack extension, and rejects the information of ghost areas to avoid artifacts via fusion masks. Experiment results show that the proposed algorithm can remove ghost artifacts accurately for both static and handheld cameras, remain robust to scenes with complex motion and keep low complexity over recent advances including patch based method and rank minimization based method by 20.4% and 63.6% time savings on average.

本文言語English
ホスト出版物のタイトル2017 IEEE International Conference on Image Processing, ICIP 2017 - Proceedings
出版社IEEE Computer Society
ページ2244-2248
ページ数5
ISBN(電子版)9781509021758
DOI
出版ステータスPublished - 2018 2 20
イベント24th IEEE International Conference on Image Processing, ICIP 2017 - Beijing, China
継続期間: 2017 9 172017 9 20

出版物シリーズ

名前Proceedings - International Conference on Image Processing, ICIP
2017-September
ISSN(印刷版)1522-4880

Other

Other24th IEEE International Conference on Image Processing, ICIP 2017
国/地域China
CityBeijing
Period17/9/1717/9/20

ASJC Scopus subject areas

  • ソフトウェア
  • コンピュータ ビジョンおよびパターン認識
  • 信号処理

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