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2 September 2014 Ghost detection and removal based on super-pixel grouping in exposure fusion
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Proceedings Volume 9284, 7th International Symposium on Advanced Optical Manufacturing and Testing Technologies: Optoelectronics Materials and Devices for Sensing and Imaging; 928418 (2014) https://doi.org/10.1117/12.2070620
Event: 7th International Symposium on Advanced Optical Manufacturing and Testing Technologies (AOMATT 2014), 2014, Harbin, China
Abstract
A novel multi-exposure images fusion method for dynamic scenes is proposed. The commonly used techniques for high dynamic range (HDR) imaging are based on the combination of multiple differently exposed images of the same scene. The drawback of these methods is that ghosting artifacts will be introduced into the final HDR image if the scene is not static. In this paper, a super-pixel grouping based method is proposed to detect the ghost in the image sequences. We introduce the zero mean normalized cross correlation (ZNCC) as a measure of similarity between a given exposure image and the reference. The calculation of ZNCC is implemented in super-pixel level, and the super-pixels which have low correlation with the reference are excluded by adjusting the weight maps for fusion. Without any prior information on camera response function or exposure settings, the proposed method generates low dynamic range (LDR) images which can be shown on conventional display devices directly with details preserving and ghost effects reduced. Experimental results show that the proposed method generates high quality images which have less ghost artifacts and provide a better visual quality than previous approaches.
© (2014) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Shenyu Jiang, Zhihai Xu, Qi Li, Yueting Chen, and Huajun Feng "Ghost detection and removal based on super-pixel grouping in exposure fusion", Proc. SPIE 9284, 7th International Symposium on Advanced Optical Manufacturing and Testing Technologies: Optoelectronics Materials and Devices for Sensing and Imaging, 928418 (2 September 2014); https://doi.org/10.1117/12.2070620
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