期刊
ADVANCES IN ELECTRICAL AND COMPUTER ENGINEERING
卷 20, 期 3, 页码 3-10出版社
UNIV SUCEAVA, FAC ELECTRICAL ENG
DOI: 10.4316/AECE.2020.03001
关键词
image sequence analysis; image fusion; image reconstruction; image motion analysis; image quality
资金
- Deanship of Scientific Research (DSR), University of Jeddah [UJ-02-034-DR]
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 pixel. 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 the existing state of the art methods.
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