An algorithm combining local entropy and histogram statistics was proposed in order to solve the problem that it is difficult to detect the blurred radius quickly and correctly in defocused image blind restoration.Firstly,the gray level information of blurred image was extracted by local entropy filter and straight lines were detected by Canny edge detector and Hough transform.Secondly,the straight step edges were located to compute the line spread function adopting Grubbs method and histogram feature of the parallel line area.Finally,the blurred radius could be obtained by line spread function.The experimental results show that the step edges can be located quickly and accurately when blurred radius is small,thus increasing recognition accuracy and recognition efficiency.