Research On Deblurring Method Of Motion Image Using Blind Deconvolution Based On TMS320c6748 Platform

When shooting an image outdoors,the motion of the shooting equipment and the abnormal vibration will cause the blurring of the collected image and affect the subsequent processing of the image.Motion image deblurring is a very important research direction in the field of image restoration.Sparse representation,as a research hotspot of image signal processing,has been widely studied because of its good anti-noise performance and accurate representation of images.A large number of experiments have proved the effectiveness of sparse representation theory in deblurring.However,the process of dictionary learning is complex and time-consuming,and it is difficult to transplant it into a DSP platform.Regarding the problems existing in current image deblurring algorithms,this paper carries out optimization research.The main work of this paper is as follows:(1)To overcome the shortage of high-frequency information extracted from blurred images by existing algorithms,a motion image deblurring algorithm based on non-subsampling is proposed.The high frequency part of the image is extracted by non-subsampling.According to the sensitivity of the ratio of L1 norm to L2 norm to the high frequency part,if the value is lowest,the blurring can be effectively removed.Then the algorithm is transplanted to the DSP platform for a series of experiments.The experimental results show that the algorithm transplanted to DSP can achieve satisfactory results.(2)Aiming at the problem of restoring details and robustness to noise of the proposed blind deblurring algorithm based on non-subsampling,a new blind deblurring method combining sparse representation is proposed.This method aims to improve the restoration of image details and achieve the effect of anti-noise and anti-ringing.Finally,the proposed method is compared with the two recently proposed algorithms which have better deblurring effect,and applied to artificial blurred image and aerial natural blurred image respectively.The experimental results show that the proposed algorithm has more advantages in motion image deblurring.