Image target identification method based on curvelet domain bilateral two-dimension principal component analysis

The invention discloses a synthetic aperture radar (SAR) image target identification method based on curvelet domain bilateral two-dimension principal component analysis. The method specifically comprises the following steps of: inputting images of a training sample and a test sample, and normalizing the sample images; performing curvelet transformation on the normalized samples, and extracting low-frequency sub-band coefficients of each sample which is transformed; acquiring left and right projection matrixes of characteristics according to the obtained low-frequency sub-band coefficients of the training sample; acquiring characteristic values of the training sample and the test sample by using the left and right projection matrixes which are obtained; and classifying the characteristics of the test sample by using a nearest neighbor classification method, and thus obtaining a final identification result. Compared with the prior art, the method has the advantages that the dimensionality of the characteristics is effectively reduced, high correct identification rate can be obtained, an implementation method is simple, and identification time is effectively shortened.