A Novel Successive Cancellation Method to Retrieve Sea Wave Components from Spatio-Temporal Remote Sensing Image Sequences

In this paper, we consider retrieving individual wave components in a multi-directional sea wave model. To solve this problem, a currently and commonly used method is three-dimensional discrete Fourier transform (3D DFT) on the radar image sequence. However, the uniform frequency and the uniform wavenumber in a wavenumber frequency domain can not always strictly satisfy the dispersion relation, and the spectral leakage in both temporal and spatial domains exists due to the limited analysis area selected from an image sequence. As a result, the DFT method incurs undesirable error performance in retrieving directional wave components. By deeply investigating the data structure of the multi-directional sea wave model, we obtain a new and decomposable matrix representation for processing the wave components. Then, a novel successive cancellation method is proposed to efficiently and effectively extract individual wave components, whose frequency and wavenumber rigorously satisfy the liner dispersion relation. Thus, it avoids spectral leakage in the spatial domain. The algorithm is evaluated by using linear synthetic wave image sequences. The validity of the proposed novel algorithm is verified by comparing the retrieved parameters of amplitude, phase, and direction of the individual wave components with the simulated parameters as well as those obtained by using the 3D DFT method. In addition, the reconstructed sea field using the retrieved wave components is also compared with the simulated remote sensing images as well as those attained using the inverse 3D DFT method. All the simulation results demonstrate that our proposed algorithm is more effective and has better performance for retrieving individual wave components from the spatio-temporal remote sensing image sequences than the 3D DFT method.