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5 February 2019 Algorithm of multiexposure image fusion with detail enhancement and ghosting removal
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Abstract
Multiexposure image fusion is an effective method for depicting a high dynamic range display of target scenes. However, the loss of local details and ghosting artifacts in fusion images has not yet been well resolved in the existing research. To solve these problems, a multiexposure image fusion algorithm with detail enhancement and ghosting removal is proposed. First, the exposure brightness and chromaticity information in YIQ color space are used to measure weight maps. When the captured scene is dynamic with moving objects, the weight maps are refined to remove ghosting artifacts based on the image difference and superpixel segmentation. Finally, an improved Laplacian pyramid fusion framework is proposed to achieve image fusion with detail enhancement. The experimental results demonstrate the effectiveness of the proposed method in terms of both visual quality and objective evaluation and show that the proposed algorithm can preserve more details and can remove ghosting artifacts effectively.
© 2019 SPIE and IS&T 1017-9909/2019/$25.00 © 2019 SPIE and IS&T
Zhong Qu, Xu Huang, Kuo Chen, and Ling Liu "Algorithm of multiexposure image fusion with detail enhancement and ghosting removal," Journal of Electronic Imaging 28(1), 013022 (5 February 2019). https://doi.org/10.1117/1.JEI.28.1.013022
Received: 29 June 2018; Accepted: 8 January 2019; Published: 5 February 2019
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