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MOU Xingang, CUI Jian, ZHOU Xiao. Infrared Image Non-uniformity Correction Algorithm Based on Full Convolutional Network[J]. Infrared Technology , 2022, 44(1): 21-27.
Citation: MOU Xingang, CUI Jian, ZHOU Xiao. Infrared Image Non-uniformity Correction Algorithm Based on Full Convolutional Network[J]. Infrared Technology , 2022, 44(1): 21-27.
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Infrared Image Non-uniformity Correction Algorithm Based on Full Convolutional Network

  • School of Mechanical and Electronic Engineering, Wuhan University of Technology, Wuhan 430070, China

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  • Received Date: February 07, 2021
  • Revised Date: April 24, 2021
    Graphical Abstract
    • Abstract
  • The infrared imaging system will still exhibit non-uniform noise after two-point correction. An infrared image non-uniformity correction algorithm based on a fully convolutional deep learning network was proposed in response to this problem. This algorithm combines the subnetwork and main network for non-uniformity correction. The network contains a nonuniformity-level estimation subnetwork. After inputting the infrared image with non-uniform noise into the non-uniformity level estimation subnetwork, the outputted non-uniformity level estimation map is input into the main network together with the original noise infrared image. The non-uniformity level estimated map generated by the subnetwork prevents the network from overfitting only for the non-uniformity of the same grade. After experimental verification, the algorithm overcomes the problem of edge blur generated by the scene-based algorithm. The algorithm will not appear blurred, the images have high definition and rich details, and the quality of images is good.
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    • References (16)
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