In order to see the differences of Mueller matrices in Fig. 4 more clearly, we redraw the elements , , and from Figs. 4(a), 4(b), and 4(c) with a different color map, shown in Figs. 6(a1), 6(b1), and 6(c1), respectively. To quantitatively assess the effectiveness of the above restoration process, we extract three rows of data from Mueller matrix images, as shown in Figs. 6(a1), 6(b1), and 6(c1) by the horizontal red lines, and plot the values of the Mueller matrix elements , , and along the selected rows as shown in Figs. 6(a2), 6(b2), and 6(c2), respectively. In order to clearly show how the restoration works, we choose the lines far away from the center where the distortions are more serious. The mean deviations of the distorted (red lines) and the original (dark lines) , , and are 0.61, 0.41, and 0.90, respectively. And the mean deviations of the recovered (blue lines) and the original , , and are 0.08, 0.08, and 0.06, respectively. Apparently, there are significant differences between the distorted and the original , , and , but the differences between the recovered and the original Mueller matrix elements are much smaller. Such a good agreement validates the effectiveness of the restoration technique by the matrix inversion. Some minor errors remaining in the restoration are mainly because of the different optical aberrations between the objective and the GRIN lens across the field of view. In addition, Fig. 4(a) comes from just one direct measurement, but Fig. 4(c) is based on two experiments and the matrix calculation, which may introduce extra errors.