The invention discloses a low-order
decomposition method for blind
deblurring of images, and mainly aims to solve the problem that in the prior art, the
image edge and high-frequency details cannot be recovered favorably during blind
deblurring of images. The implementation process comprises the following steps of: (1) pre-restoring a blurred image b by using a
frequency domain iteration method to obtain an iteration image and a blurring kernel i=1,2,3...45; (2) normalizing each image in the iteration image i=1,2,3...45 to obtain a normalized iteration image i=1,2,3...45; (3) pulling each image of the normalized iteration image i=1,2,3...45 into a column, and forming high-dimensional data M in the order of i=1,2,3...45; (4) calculating a low-order matrix L of the high-dimensional data M; (5) restoring each column in the low-order matrix L into an image to obtain a low-order image ri, i=1,2,3...45; and (6) carrying out mean
processing on the low-order image ri, i=1,2,3...45 to obtain a final sharp image F. By adopting the method, the iterated image information can be fully utilized, the
ring effect is removed, and sharp images with abundant details can be restored. The method can be used for blind
deblurring of various blurred images.