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Versatile visible and near-infrared image fusion based on high visibility area selection

[+] Author Affiliations
Takashi Shibata

Tokyo Institute of Technology, Graduate School of Science and Engineering, Department of Mechanical and Control Engineering, 2-12-1 O-okayama, Meguro-ku, Tokyo 152-8550, Japan

NEC Corporation, 1753 Shimonumabe, Nakahara-Ku, Kawasaki, Kanagawa 211-8666, Japan

Masayuki Tanaka

Tokyo Institute of Technology, Graduate School of Science and Engineering, Department of Mechanical and Control Engineering, 2-12-1 O-okayama, Meguro-ku, Tokyo 152-8550, Japan

Masatoshi Okutomi

NEC Corporation, 1753 Shimonumabe, Nakahara-Ku, Kawasaki, Kanagawa 211-8666, Japan

J. Electron. Imaging. 25(1), 013016 (Jan 26, 2016). doi:10.1117/1.JEI.25.1.013016
History: Received July 16, 2015; Accepted December 17, 2015
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Abstract.  We present an image fusion algorithm for a visible image and a near-infrared image. The proposed algorithm synthesizes a fused image that includes high-visibility information of both images while reducing artifacts caused by geometric and illumination inconsistencies. In the proposed fusion, the high-visibility area is labeled at each pixel by global optimization based on the local visibility and inconsistency. The local visibility is evaluated using a local contrast. The inconsistency is also locally estimated based on a learning-based approach. The fused luminance is constructed using Poisson image reconstruction that preserves the gradient of the selected high-visibility areas. The proposed fusion framework has various applications, which include denoising, haze removal, and image enhancement. Experimental results show that the proposed method has comparable or even superior performance to existing methods designed for specific applications.

© 2016 SPIE and IS&T

Topics

Near infrared

Citation

Takashi Shibata ; Masayuki Tanaka and Masatoshi Okutomi
"Versatile visible and near-infrared image fusion based on high visibility area selection", J. Electron. Imaging. 25(1), 013016 (Jan 26, 2016). ; http://dx.doi.org/10.1117/1.JEI.25.1.013016


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