Detecting of multi-dim-small-target in sea or sky background based on higher-order cumulants and wavelet

Abstract

This paper describes a technology of multi-dim-small-target detection. Two-dimensional (2-D) adaptive filtering and multi-dim-small-target segmentation algorithm is suggested to enhance 2-D signals of small spatial extent embedded in additive white Gaussian noise(AWGN) and detect multi-dim-small-target in complex background. The coefficients of the adaptive filter converge to a special 2-D slice of the fourth-order cumulant function of the input signal. The 2-D filter is called the 2-D cumulant-based adaptive enhancer (2DCBAE). And the dim-small-target segmentation algorithm is combining some theory, such as the wavelet energy transformation, image reconstruction, data fusion and self-adaptive threshold segmentation. © 2012 Springer-Verlag Berlin Heidelberg.