Acta Optica Sinica, Volume. 36, Issue 9, 910001(2016)

Infrared Image Enhancement Based on PCNN Segmentation and Fuzzy Set Theory

Su Juan*, Li Bing, and Wang Yanzhao
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  • [in Chinese]
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    To overcome the interference of the sky background in infrared image enhancement, and highlight the target in the image, an infrared image enhancement method based on pulse coupled neural network (PCNN) segmentation and fuzzy set theory is proposed. The PCNN is utilized to segment the image into sky background region and target region. The adaptive fuzzy enhancement method based on ridge type distribution is used to enhance the target region reflectance image obtained by variation Retinex, and the enhanced reflectance image and the illumination image are fused together. The local average value of target region is assigned to the sky background region, and the enhanced image is acquired by the reconstruction of the target region and the sky background region. Experimental results demonstrate that the proposed method can overcome the noise amplification problem of existing algorithm in sky region, and the enhanced images have high contrast and good visual effects.

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    Su Juan, Li Bing, Wang Yanzhao. Infrared Image Enhancement Based on PCNN Segmentation and Fuzzy Set Theory[J]. Acta Optica Sinica, 2016, 36(9): 910001

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    Paper Information

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    Received: Mar. 18, 2016

    Accepted: --

    Published Online: Sep. 9, 2016

    The Author Email: Juan Su (suj04@mails.tsinghua.edu.cn)

    DOI:10.3788/aos201636.0910001

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