Total variation image restoration for mixed blur in moving image

In order to restore the image in the video frame of a moving image, the mixed blur that combines two common blur types, motion blur and defocus blur, was discussed. Firstly, blur types were determined according to the difference in spectrum features and the Point Spread Function (PSF) was estimated quantitatively using the cepstrum analysis. Blur parameters in simulation experiments were chosen based on engineering to verify the accuracy of the cepstrum analysis in the PSF estimation method. Then, a gradient fidelity term was coupled with total variation image restoration algorithm to constrain the impact of the PSF estimation error on image restoration and the Split-Bregman algorithm that is compatible with the L¹ norm was adopted to accomplish the numerical computing in restoration algorithm. Finally, the simulation experiments and the real image restoration were carried to verify the performance of the algorithm. The results show that cepstrum analysis for estimating the PSF has an accuracy rate of 90%.The proposed algorithm can preserve edges and details, inhibit the ringing effect effectively and shows its Peak Signal to Noise Rate (PSNR) to be 28.92 dB.