De-ghosting in High Dynamic Range Imaging Based on Intensity Scaling Cue

A High Dynamic Range (HDR) image produced from a sequence of low dynamic range (LDR) images can contain motion artefacts (ghosting) if the scene contains moving objects. Conventional de-ghosting methods first detect moving objects in the scene, and then either remove those moving objects totally o...

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Main Authors: SHIM, S.-O, ALHARBI, S., KHAN, I. R., AZIZ, W.
Format: Article
Language:English
Published: Stefan cel Mare University of Suceava 2020-08-01
Series:Advances in Electrical and Computer Engineering
Subjects:
Online Access:http://dx.doi.org/10.4316/AECE.2020.03001
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spelling doaj-2d5f402fa9d8413fb3f9389ab5f4ba8d2020-11-25T03:41:58ZengStefan cel Mare University of SuceavaAdvances in Electrical and Computer Engineering1582-74451844-76002020-08-0120331010.4316/AECE.2020.03001De-ghosting in High Dynamic Range Imaging Based on Intensity Scaling CueSHIM, S.-OALHARBI, S.KHAN, I. R.AZIZ, W.A High Dynamic Range (HDR) image produced from a sequence of low dynamic range (LDR) images can contain motion artefacts (ghosting) if the scene contains moving objects. Conventional de-ghosting methods first detect moving objects in the scene, and then either remove those moving objects totally or reconstruct them. However, these methods are computationally expensive. This paper proposes a de-ghosting method that does not require explicit detection of moving regions. First, the ratio between camera exposure times of a target image and a reference image, which is called the intensity scaling factor in this paper, is computed. Since the information about camera exposure time is not available always, we propose a novel method to estimate the intensity scaling factor from non-saturated and non-moving pixels. Then, the estimated scaling factor is used as a cue to label every pixel in the target image as either static or moving pixel. Finally, the values of moving pixels are corrected with their expected values which can be estimated from the intensity scaling factor. Experimental results show that the proposed method generates more accurate ghost-free HDR images than the existing state of the art methods.http://dx.doi.org/10.4316/AECE.2020.03001image sequence analysisimage fusionimage reconstructionimage motion analysisimage quality
collection DOAJ
language English
format Article
sources DOAJ
author SHIM, S.-O
ALHARBI, S.
KHAN, I. R.
AZIZ, W.
spellingShingle SHIM, S.-O
ALHARBI, S.
KHAN, I. R.
AZIZ, W.
De-ghosting in High Dynamic Range Imaging Based on Intensity Scaling Cue
Advances in Electrical and Computer Engineering
image sequence analysis
image fusion
image reconstruction
image motion analysis
image quality
author_facet SHIM, S.-O
ALHARBI, S.
KHAN, I. R.
AZIZ, W.
author_sort SHIM, S.-O
title De-ghosting in High Dynamic Range Imaging Based on Intensity Scaling Cue
title_short De-ghosting in High Dynamic Range Imaging Based on Intensity Scaling Cue
title_full De-ghosting in High Dynamic Range Imaging Based on Intensity Scaling Cue
title_fullStr De-ghosting in High Dynamic Range Imaging Based on Intensity Scaling Cue
title_full_unstemmed De-ghosting in High Dynamic Range Imaging Based on Intensity Scaling Cue
title_sort de-ghosting in high dynamic range imaging based on intensity scaling cue
publisher Stefan cel Mare University of Suceava
series Advances in Electrical and Computer Engineering
issn 1582-7445
1844-7600
publishDate 2020-08-01
description A High Dynamic Range (HDR) image produced from a sequence of low dynamic range (LDR) images can contain motion artefacts (ghosting) if the scene contains moving objects. Conventional de-ghosting methods first detect moving objects in the scene, and then either remove those moving objects totally or reconstruct them. However, these methods are computationally expensive. This paper proposes a de-ghosting method that does not require explicit detection of moving regions. First, the ratio between camera exposure times of a target image and a reference image, which is called the intensity scaling factor in this paper, is computed. Since the information about camera exposure time is not available always, we propose a novel method to estimate the intensity scaling factor from non-saturated and non-moving pixels. Then, the estimated scaling factor is used as a cue to label every pixel in the target image as either static or moving pixel. Finally, the values of moving pixels are corrected with their expected values which can be estimated from the intensity scaling factor. Experimental results show that the proposed method generates more accurate ghost-free HDR images than the existing state of the art methods.
topic image sequence analysis
image fusion
image reconstruction
image motion analysis
image quality
url http://dx.doi.org/10.4316/AECE.2020.03001
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AT khanir deghostinginhighdynamicrangeimagingbasedonintensityscalingcue
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