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Making use the prior knowledge that higher order cumulant and wavlet transformation methods are combined, which is used in the multi-dim-small target detection with the Gaussian noise and natural background. In this paper, a method of magnifying image based on two dimension discrete wavelet is introduced. Comparing with traditional interpolation methods, it not only enhanced resolution of the aero-image, but maintained the detail character of the image. Experiment results have shown that it is good method for enhancing aero-image. The same aerial image is magnified with above-mentioned wavelet-based algorithms, conventional bilinear interpolation and tri-spline sampling interpolation algorithm separately. The values of mean gradient on three graphs are calculated using three approach, they are 6.31, 7.43 and 8.45. In accordance with the result, the value of the magnified image by this method is largest.

A novel two-dimensional (2-D) adaptive filtering algorithm to enhance 2-D signals of small spatial extent embedded in white Gaussian noise and a variety of outstanding modern digital signal processing methods are combined in background segmentation. The coefficients of the adaptive filter converge to a special 2-D slice of the fourth-order cumulant function of the input signal. The proposed algorithm is called the 2-D cumulant adaptive enhancer (2DCAE). And the methods in background segmentation is combining the wavelet energy transformation, data integration and threshold segmentation.