1. A method comprising: obtaining a blurred image B, being a product of a blur kernel k applied to an original image I, wherein B and I are matrices representing pixel image arrays and k is a kernel of a matrix; calculating f θ (x)=R d*Pθ(B) (x) for every angle θ, wherein R denotes an autocorrelation operator, P θ denotes a projection operator of a two dimensional signal into one dimension based on angle θ, and d denotes a one dimensional differentiation filter applied to a product of the projection operator P θ and the blurred image B; setting support parameters s θ to argmin x f θ (x); estimating |{circumflex over (k)}| 2 denoting a spectral power of the blur kernel based on a given support parameter; estimating the blur kernel k using a phase retrieval algorithm, based on the estimated spectral power of the blur kernel |{circumflex over (k)}| 2 ; updating the support parameters s θ to argmax x (R Pθ(k) (x)>a·max(R Pθ(k) )), wherein a is constant number; and repeating the estimating of the spectral power |{circumflex over (k)}| 2 , the estimating of the kernel and the updating of the support parameters s θ in an expectation maximization (EM) procedure, to yield the blur kernel k.