Li Junli, Chu Chengxi. Identification of motion blur direction from motion blurred image by directional derivation and block statistics[J]. Journal of Image and Graphics, 2013, 18(7): 776-782. DOI: 10.11834/jig.20130708.
The basic idea of identifying the direction of motion blurring by directional derivatives is that the original image is an isotropic first-order Markov random process. However
the real result are not good. The main reason is that the images do not meet this assumption strictly. Judging from the entire image
the shape of the objects
flat areas
and some other factors tend to weaken the physical premise
and cause inaccurate calculation result of the differential image. In this paper
we propose an optimization method. First
multiple feature blocks are extracted via the image local variance
and then the statistical results of the motion blur direction identification from every block are retrieved. The experimental results show that our method can still obtain good identification accuracy even when the error of the identification of traditional directional derivative method is big.