Estimation Method of Blurred Parameters in Moving Blurred Image

Abstract

In order to improve the quality of image restoration and remove the blur caused by motion in the image, a blurred parameter recognition algorithm with point spread function is proposed. This algorithm combines the Fourier spectrum of the image with the edge detection based on phase consistency and identifies the blurred angle by determining the direction of the edge of the center bright stripe. Then bilinear interpolation is used to generate the sub-pixel image of the spectrum, calculate the distance between the dark bands, and estimate the blurred length. Experimental results show that, compared with the traditional algorithm, the proposed method can not only obtain higher precision of blurred angle and blurred length, but also have better stability, and can correctly detect blurred parameters of blurred images with different scales and contents.

A Survey on Blind De-Blurring of Digital Image

“…Then bilinear interpolation is employed to produce the sub_pixel image of the spectrum, measure the distance among the dark strips, and estimate the blurred length. This method produced higher precision of blurred angle and blurred length, better stability, and correctly detect blurred parameters of blurred images [10]. Khan and Yin presented a new blind deblurring schema for images that were distorted via arbitrary PSFs.…”