4 February 2015 Feature-based multiexposure image-sequence fusion with guided filter and image alignment
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Abstract
Multiexposure fusion images have a higher dynamic range and reveal more details than a single captured image of a real-world scene. A clear and intuitive feature-based fusion technique for multiexposure image sequences is conceptually proposed. The main idea of the proposed method is to combine three image features [phase congruency (PC), local contrast, and color saturation] to obtain weight maps of the images. Then, the weight maps are further refined using a guided filter which can improve their accuracy. The final fusion result is constructed using the weighted sum of the source image sequence. In addition, for multiexposure image-sequence fusion involving dynamic scenes containing moving objects, ghost artifacts can easily occur if fusion is directly performed. Therefore, an image-alignment method is first used to adjust the input images to correspond to a reference image, after which fusion is performed. Experimental results demonstrate that the proposed method has a superior performance compared to the existing methods.
© 2015 SPIE and IS&T
Liang Xu, Junping Du, Zhenhong Zhang, "Feature-based multiexposure image-sequence fusion with guided filter and image alignment," Journal of Electronic Imaging 24(1), 013022 (4 February 2015). https://doi.org/10.1117/1.JEI.24.1.013022 . Submission:
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