9 November 2016 Guided filter-based fusion method for multiexposure images
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It is challenging to capture a high-dynamic range (HDR) scene using a low-dynamic range camera. A weighted sum-based image fusion (IF) algorithm is proposed so as to express an HDR scene with a high-quality image. This method mainly includes three parts. First, two image features, i.e., gradients and well-exposedness are measured to estimate the initial weight maps. Second, the initial weight maps are refined by a guided filter, in which the source image is considered as the guidance image. This process could reduce the noise in initial weight maps and preserve more texture consistent with the original images. Finally, the fused image is constructed by a weighted sum of source images in the spatial domain. The main contributions of this method are the estimation of the initial weight maps and the appropriate use of the guided filter-based weight maps refinement. It provides accurate weight maps for IF. Compared to traditional IF methods, this algorithm avoids image segmentation, combination, and the camera response curve calibration. Furthermore, experimental results demonstrate the superiority of the proposed method in both subjective and objective evaluations.
© 2016 Society of Photo-Optical Instrumentation Engineers (SPIE)
Xinglin Hou, Xinglin Hou, Haibo Luo, Haibo Luo, Feng Qi, Feng Qi, Peipei Zhou, Peipei Zhou, } "Guided filter-based fusion method for multiexposure images," Optical Engineering 55(11), 113101 (9 November 2016). https://doi.org/10.1117/1.OE.55.11.113101 . Submission:


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