Multiple rank regression base method for the classification of SAR images

Recognizing targets in synthetic aperture radar (SAR) images is an important, yet challenging problem in SAR image interpretation. In traditional methods, the 2-D image data is rearranged into vectors and regressed to its label by a vector where the structure information is lost. Multiple rank regression (MRR) method directly manipulation on matrix data by applying a multiple-rank left projecting vectors and right projecting vectors, and the matrix data can be regressed to its label for each category. In this paper, a multiple rank regression (MRR) based method is developed for the classification of SAR images. Firstly, SAR image samples are preprocessed to weak the nonideal factors, then train image samples are used to train the regression vectors for each class. In the test stage, the test image is regression by the trained vectors and is classified to the class with the highest regression label. Experimental results based on the moving and stationary target acquisition and recognition database verified the effectiveness of the proposed method.