Abstract
This paper relates to the newly developed empirical mode decomposition (EMD) and an effective algorithm for removing noise in sonar images utilizing EMD method is also presented. The EMD approach, with the basis of decomposition derived from the data, proved to be intuitive, direct and adaptive. As a result, EMD is quite suitable for analyzing nonlinear and non-stationary data. Sonar images can be decomposed into a series of modes whose characteristic space scale defined by the space lapse between extrema is different. The noise removal of sonar images is implemented by smearing the modes blurred by noise in the spatial domain. Different from previous works, the sifting process of EMD is realized using h-extrema transform to detect regional extrema and thanks to radial basis function for surface interpolation. Application to sonar images has shown that the performance of the algorithm is satisfactory in both noise removal and edge preservation.
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