一种基于表面散射相似度的SAR图像极化增强方法

针对传统极化增强在多类目标增强和极化信息保持方面存在的不足，该文基于表面散射的相似度提出了一种新的极化增强方法。该方法根据目标表面散射的相似度，对不同散射类型的目标相干矩阵乘以不同实系数，从而增大了表面散射的目标与其它散射的目标的对比差异。同时由于该方法将表征目标的相干矩阵作为整体进行运算，因而保持了目标的极化信息。最后利用NASA SIR-C/X-SAR实测极化数据验证了该方法的有效性。

A New Method of Polarimetric Target Enhancement Based on Surface Scattering Similarity Parameter

In order to overcome the insufficiency of traditional algorithms in multi-target enhancement and polarimetric signature preservation, a new method is proposed to enhance targets in polarimetric SAR imagery. Based on the similarity parameter between target scattering matrix and surface scattering matrix, the coherency matrix of random target corresponding to different scattering mechanisms is multiplied by relevant real coefficient, thus it enlarges the otherness between surface scattering targets and other scattering targets. As coherency matrix is operated as a whole in this method, it does not change the relationship between the elements of coherency matrix and then preserves polarimetric information in SAR imagery. Utilizing fully polarimetric data obtained by SIR-C/X-SAR to test this method, the result is satisfactory.