In this paper, we propose a novel ship detection method based on multi-visual features after analyzing the characteristics of ship in the sea. According to the principal of the visual contrast, brightness and orientation saliency map of ship object are respectively generated, and then they are integrated to obtain the total saliency map. In addition to the brightness and orientation of the ship objects, the method doesn’t use other prior knowledge of them. In ship detection experiment, the experimental results prove our method can effectively concentrate on the ship objects regardless of their size and brightness, and thereby improve the capacity of visual attention in complex scene. Thus, the design idea of our method is verified.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Multi-Visual Features Based Ship Detection in Remote Sensing Images



    Erschienen in:

    Erscheinungsdatum :

    12.09.2014


    Format / Umfang :

    5 pages




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




    Multi-layer Sparse Coding Based Ship Detection for Remote Sensing Images

    Li, Zimeng / Yang, Daiqin / Chen, Zhenzhong | IEEE | 2015


    USDet:Unknown Ship Detection Based on Remote Sensing Optical Images

    Cheng, Wei / Gong, Tengfei / Gong, Dongdong et al. | IEEE | 2024


    S-CNN-BASED SHIP DETECTION FROM HIGH-RESOLUTION REMOTE SENSING IMAGES

    R. Zhang / J. Yao / K. Zhang et al. | DOAJ | 2016

    Freier Zugriff

    Marine Vision-Based Situational Automatic Ship Detection Using Remote Sensing Images

    Haldorai, Anandakumar / R, Babitha Lincy / Murugan, Suriya et al. | Springer Verlag | 2024


    Ship object detection in remote sensing images using convolutional neural networks

    Huang, Jie / Jiang, Zhiguo / Zhang, Haopeng et al. | British Library Online Contents | 2017