Image Restoration by Variable Splitting based on Total Variant Regularizer

The aim of image restoration is to obtain a higher quality desired image from a degraded one. In this strategy, an image inpainting method fills the degraded or lost area of the image by an appropriate information. This is achieved in such a way that the image obtained is undistinguishable for a casual person who is unfamiliar with the original image. In this work, different images are degraded by two procedures; one is to blur and to add noise to the original image, and the other one is to lose a percentage of the original image pixels. Then the degraded image is restored by the proposed method and also two state-of-art methods. For image restoration, it is required to use the optimization methods. In this work, we use a linear restoration method based upon the total variation regularizer. The variable of optimization problem is split, and the new optimization problem is then solved using the Lagrangian augmented method. The experimental results obtained show that the proposed method is faster, and the restored images have a higher quality compared to the other methods.