Robust ghost-free high-dynamic-range imaging by visual salience based bilateral motion detection and stack extension based exposure fusion

Zijie Wang, Qin Liu, Takeshi Ikenaga

Research output: Contribution to journalArticle

Abstract

High-dynamic-range imaging (HDRI) technologies aim to extend the dynamic range of luminance against the limitation of camera sensors. Irradiance information of a scene can be reconstructed by fusing multiple low-dynamic-range (LDR) images with different exposures. The key issue is removing ghost artifacts caused by motion of moving objects and handheld cameras. This paper proposes a robust ghost-free HDRI algorithm by visual salience based bilateral motion detection and stack extension based exposure fusion. For ghost areas detection, visual salience is introduced to measure the differences between multiple images; bilateral motion detection is employed to improve the accuracy of labeling motion areas. For exposure fusion, the proposed algorithm reduces the discontinuity of brightness 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 rank minimization based method and patch based method by 63.6% and 20.4% time savings averagely.

Original languageEnglish
Pages (from-to)2266-2274
Number of pages9
JournalIEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences
VolumeE100A
Issue number11
DOIs
Publication statusPublished - 2017 Nov 1

Fingerprint

Range Imaging
Motion Detection
High Dynamic Range
Fusion
Fusion reactions
Camera
Dynamic Range
Imaging techniques
Motion
Cameras
Luminance
Range Image
Irradiance
Brightness
Moving Objects
Low Complexity
Mask
Labeling
Patch
Discontinuity

Keywords

  • Exposure fusion
  • Ghost removal
  • High-dynamic-range imaging (HDRI)
  • Motion detection
  • Visual salience

ASJC Scopus subject areas

  • Signal Processing
  • Computer Graphics and Computer-Aided Design
  • Electrical and Electronic Engineering
  • Applied Mathematics

Cite this

@article{3dcf6942e74b4bd0a56895dd21237e05,
title = "Robust ghost-free high-dynamic-range imaging by visual salience based bilateral motion detection and stack extension based exposure fusion",
abstract = "High-dynamic-range imaging (HDRI) technologies aim to extend the dynamic range of luminance against the limitation of camera sensors. Irradiance information of a scene can be reconstructed by fusing multiple low-dynamic-range (LDR) images with different exposures. The key issue is removing ghost artifacts caused by motion of moving objects and handheld cameras. This paper proposes a robust ghost-free HDRI algorithm by visual salience based bilateral motion detection and stack extension based exposure fusion. For ghost areas detection, visual salience is introduced to measure the differences between multiple images; bilateral motion detection is employed to improve the accuracy of labeling motion areas. For exposure fusion, the proposed algorithm reduces the discontinuity of brightness 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 rank minimization based method and patch based method by 63.6{\%} and 20.4{\%} time savings averagely.",
keywords = "Exposure fusion, Ghost removal, High-dynamic-range imaging (HDRI), Motion detection, Visual salience",
author = "Zijie Wang and Qin Liu and Takeshi Ikenaga",
year = "2017",
month = "11",
day = "1",
doi = "10.1587/transfun.E100.A.2266",
language = "English",
volume = "E100A",
pages = "2266--2274",
journal = "IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences",
issn = "0916-8508",
publisher = "Maruzen Co., Ltd/Maruzen Kabushikikaisha",
number = "11",

}

TY - JOUR

T1 - Robust ghost-free high-dynamic-range imaging by visual salience based bilateral motion detection and stack extension based exposure fusion

AU - Wang, Zijie

AU - Liu, Qin

AU - Ikenaga, Takeshi

PY - 2017/11/1

Y1 - 2017/11/1

N2 - High-dynamic-range imaging (HDRI) technologies aim to extend the dynamic range of luminance against the limitation of camera sensors. Irradiance information of a scene can be reconstructed by fusing multiple low-dynamic-range (LDR) images with different exposures. The key issue is removing ghost artifacts caused by motion of moving objects and handheld cameras. This paper proposes a robust ghost-free HDRI algorithm by visual salience based bilateral motion detection and stack extension based exposure fusion. For ghost areas detection, visual salience is introduced to measure the differences between multiple images; bilateral motion detection is employed to improve the accuracy of labeling motion areas. For exposure fusion, the proposed algorithm reduces the discontinuity of brightness 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 rank minimization based method and patch based method by 63.6% and 20.4% time savings averagely.

AB - High-dynamic-range imaging (HDRI) technologies aim to extend the dynamic range of luminance against the limitation of camera sensors. Irradiance information of a scene can be reconstructed by fusing multiple low-dynamic-range (LDR) images with different exposures. The key issue is removing ghost artifacts caused by motion of moving objects and handheld cameras. This paper proposes a robust ghost-free HDRI algorithm by visual salience based bilateral motion detection and stack extension based exposure fusion. For ghost areas detection, visual salience is introduced to measure the differences between multiple images; bilateral motion detection is employed to improve the accuracy of labeling motion areas. For exposure fusion, the proposed algorithm reduces the discontinuity of brightness 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 rank minimization based method and patch based method by 63.6% and 20.4% time savings averagely.

KW - Exposure fusion

KW - Ghost removal

KW - High-dynamic-range imaging (HDRI)

KW - Motion detection

KW - Visual salience

UR - http://www.scopus.com/inward/record.url?scp=85033464579&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85033464579&partnerID=8YFLogxK

U2 - 10.1587/transfun.E100.A.2266

DO - 10.1587/transfun.E100.A.2266

M3 - Article

AN - SCOPUS:85033464579

VL - E100A

SP - 2266

EP - 2274

JO - IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences

JF - IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences

SN - 0916-8508

IS - 11

ER -