A Fast Iterative Pursuit Algorithm in Robust Face Recognition Based on Sparse Representation
Figure 2
Error between an occluded image and a “clean” one. We reshape the pixels in the two samples (a) into vectors and calculate the difference (b). Obviously, the distribution of error is like a comb, which indicates that the error exists in a few pixels and the others are “clean.”
