Blind deblurring of foreground-background images

This paper presents a method for deblurring an image consisting of two layers (a foreground layer and a background layer) which have suffered different, unknown blurs. This is a situation of practical interest. For example, it is common to find images in which we have a foreground object (e.g. a car) which has motion blur while the background is sharp (or vice-versa), or in which a foreground object and the background have different out-of-focus blurs. We develop a model for this foreground + background degradation, and extend a previously introduced blind deblurring method to deal with this situation. As in the original blind deblurring method, the method presented here does not impose any strong constraints on the blurring filters. The method is almost completely blind, requiring, form the user, just a coarse indication of which are the foreground and background areas of the image. The method has been tested with synthetic degradations and with real-life photos. We present some of the results. In all the experiments, the method was able to reasonably recover, from single degraded images: the complete deblurred image, the deblurred foreground and background images, and a mask providing the segmentation between foreground and background.