A response distortion correction method of Intensified Complementary Metal Oxide Semiconductor (ICMOS) camera is proposed. First, the Fixed Pattern Noise (FPN) is removed from the original input image captured by the ICMOS camera. Second, the response correction using the traditional method, i.e., the polynomial fitting technique, is considered to eliminate the error to some extent. Third, a response correction using the machine learning-based method is proposed to decrease the error further. A kind of Improve Adaptive Genetic Algorithm-Support Vector Regression (IAGA-SVR) is designed to improve the computation effect of SVR. The inputs of IAGA-SVR include the manufacturing and response parameters of ICMOS camera; the output of it is the error compensation item. Extensive experiment results have shown that our proposed method can improve the response correction accuracy than the traditional and other improved optimal algorithm-based methods.


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    Titel :

    Response Distortion Correction of ICMOS Camera Using Improved Support Vector Regression


    Weitere Titelangaben:

    Lect. Notes Electrical Eng.


    Beteiligte:
    Long, Shengzhao (Herausgeber:in) / Dhillon, Balbir S. (Herausgeber:in) / Liu, Haoting (Autor:in) / Ge, Jianyue (Autor:in) / Yang, Shaohua (Autor:in) / Li, Gang (Autor:in) / Liu, Lu (Autor:in)

    Kongress:

    International Conference on Man-Machine-Environment System Engineering ; 2023 ; Beijing, China October 20, 2023 - October 23, 2023



    Erscheinungsdatum :

    05.09.2023


    Format / Umfang :

    8 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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