Blind deconvolution of video sequences

We present a new blind deconvolution method for video sequence. It is derived following an inverse problem approach in a Bayesian framework. This method exploits the temporal continuity of both object and PSF Combined with edge-preserving spatial regularization, a temporal regularization constrains the blind deconvolution problem, improving its effectiveness and its robustness. We demonstrate these improvements by processing various real video sequences obtained by different imaging techniques.