An iterative blind image restoration algorithm based on Self-deconvolution and Incremental Wiener Filter (SDIWF-IBD) is proposed. The self-deconvolution estimation for a Point Spread Function(PSF) is applied to Iterative Blind Deconvolution(IBD) to estimating exactly the frequency domain of the PSF. The incremental Wiener filter is used in the image estimation of IBD to keep the algorithm convergence steady. To further control the convergency, an in-iterative acceleration is suggested to control the speed of algorithm convergence and reduce total external iteration. Experimental results indicate that more details are recovered in the restoration image with few distortions, and the algorithm is converged to a small error quickly. It concludes that the SDIWF-IBD algorithm has good restoration ability at a fast and controllable convergency speed, and is fit for applications in real-time.