The fog seriously affects the quality of UAV images and influences the performances of reconnaissance and recognition. In order to improve the effective utilization of UAV images, this paper proposes an UAV image dehazing method based on the optimum of image quality assessment. By the combination of three image quality assessment parameters, including information entropy, standard deviation and image Fourier amplitude, the comprehensive image quality assessment function is established. The best global atomspheric transmission value corresponds to maximum of accessing function. The experiments shows that the UAV image dehazing based on the optimum of image quality assessment has low computational complexity, simple operation and good real-time performance, and the obtained dehazing image has clear visual effects and minor result errors.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    An Image Dehazing Method Based on the Optimum of Image Quality Assessment


    Additional title:

    Lect. Notes Electrical Eng.


    Contributors:
    Wu, Meiping (editor) / Niu, Yifeng (editor) / Gu, Mancang (editor) / Cheng, Jin (editor) / Jiang, Yutong (author) / Yang, Zhonglin (author) / Zhu, Mengqi (author)

    Conference:

    International Conference on Autonomous Unmanned Systems ; 2021 ; Changsha, China September 24, 2021 - September 26, 2021



    Publication date :

    2022-03-18


    Size :

    12 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English




    Single-Image Dehazing

    Tian, Jiandong | Springer Verlag | 2021


    Prior based Single Image Dehazing using Decision Image

    Parihar, Anil Singh / Gupta, Gokul | IEEE | 2020


    Single Image Dehazing via Image Generating

    Zhang, Shengdong / Yao, Jian / Garcia, Edel B. | British Library Conference Proceedings | 2018


    Image dehazing based on haziness analysis

    Guo, F. / Tang, J. / Cai, Z. X. | British Library Online Contents | 2014


    DAY/NIGHT UNCONSTRAINED IMAGE DEHAZING

    Santra, Sanchayan / Chanda, Bhabatosh | British Library Conference Proceedings | 2016