The ability of synthetic aperture radar (SAR) to capture maritime phenomena is widely acknowledged. However, ocean SAR scene automatic classification remains challenging due to speckle noise interference, the nonlinearities and poor distinguishability of different geophysical phenomena. Kernel entropy component analysis (KECA) was recently proposed as a feature extraction approach. It is capable of handling nonlinear data and...