The detection of the wake can provide substantial information about a ship, such as its size, direction, and speed of movement. In general though, ship-generated wakes in synthetic aperture radar images are associated with high sea clutter, which will cause some deterioration in the detection performance. Therefore, a wavelet correlator, based on an orthogonal basis function, is adopted. Three highpass images - horizontal, vertical, and diagonal direction - are generated for each resolution scale, followed by a process to correlate among the moduli of different scale modulus images formed from the three highpass images. The output of the correlation process is highly representative at the ship's wake edges. Comparisons with other methods indicate the superior performance of the present approach, in that not only can the wakes be detected, but their V-shaped pattern is well preserved. The second stage involves the application of the Radon transform technique to an estimation of the V-opening angle from the detected ship wakes. Ship-generated wake edges are found to be the local maxima in the wavelet transform method of several adjacent scales, and hence, the wake edge will be enhanced in the reconstructed data. The background noise is also greatly reduced. In particular, the process of spatial correlation is found to be critical. Compared to a direct Radon transform, the proposed scheme is demonstrated to be much more effective in terms of efficiency, as well as reliability, for ship wake detection in noisy backgrounds.


    Access

    Access via TIB

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    The application of wavelets correlator for ship wake detection in SAR images


    Contributors:
    Kuo, Jin-Min (author) / Chen, K.S. (author)

    Published in:

    Publication date :

    2003


    Size :

    6 Seiten, 16 Quellen




    Type of media :

    Article (Journal)


    Type of material :

    Print


    Language :

    English




    Ship heading and velocity analysis by wake detection in SAR images

    Graziano, Maria Daniela / D’Errico, Marco / Rufino, Giancarlo | Elsevier | 2016


    Automatic Ship Wake Detection from Sentinel-2 Images by Deep Learning

    Prete, Roberto Del / Renga, Alfredo / Graziano, Maria Daniela et al. | TIBKAT | 2023


    Ship heading and velocity analysis by wake detection in SAR images

    Graziano, Maria Daniela | Online Contents | 2016


    Ship heading and velocity analysis by wake detection in SAR images

    Graziano, Maria Daniela | Online Contents | 2016


    Ship wake

    Akimoff, N.W. | Engineering Index Backfile | 1931