Imaging Components, Systems, and Processing

Guided filter-based fusion method for multiexposure images

[+] Author Affiliations
Xinglin Hou, Peipei Zhou

Chinese Academy of Sciences, Shenyang Institute of Automation, No. 114 Nanta Street, Shenhe District, Shenyang 110016, China

Chinese Academy of Sciences, Key Laboratory of Opto-Electronic Information Processing, No. 114 Nanta Street, Shenhe District, Shenyang 110016, China

University of Chinese Academy of Sciences, No. 19A Yuquan Road, Beijing 100049, China

Haibo Luo, Feng Qi

Chinese Academy of Sciences, Shenyang Institute of Automation, No. 114 Nanta Street, Shenhe District, Shenyang 110016, China

Chinese Academy of Sciences, Key Laboratory of Opto-Electronic Information Processing, No. 114 Nanta Street, Shenhe District, Shenyang 110016, China

Opt. Eng. 55(11), 113101 (Nov 09, 2016). doi:10.1117/1.OE.55.11.113101
History: Received May 3, 2016; Accepted October 12, 2016
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Abstract.  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.

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© 2016 Society of Photo-Optical Instrumentation Engineers

Citation

Xinglin Hou ; Haibo Luo ; Feng Qi and Peipei Zhou
"Guided filter-based fusion method for multiexposure images", Opt. Eng. 55(11), 113101 (Nov 09, 2016). ; http://dx.doi.org/10.1117/1.OE.55.11.113101


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