  We present a highly efficient blind restoration method to remove mild blur in
natural images. Contrary to the mainstream, we focus on removing slight blur
that is often present, damaging image quality and commonly generated by small
out-of-focus, lens blur, or slight camera motion. The proposed algorithm first
estimates image blur and then compensates for it by combining multiple
applications of the estimated blur in a principled way. To estimate blur we
introduce a simple yet robust algorithm based on empirical observations about
the distribution of the gradient in sharp natural images. Our experiments show
that, in the context of mild blur, the proposed method outperforms traditional
and modern blind deblurring methods and runs in a fraction of the time. Our
method can be used to blindly correct blur before applying off-the-shelf deep
super-resolution methods leading to superior results than other highly complex
and computationally demanding techniques. The proposed method estimates and
removes mild blur from a 12MP image on a modern mobile phone in a fraction of a
second.
