A new and general method for blind shift-variant deconvolution of biomedical images
MICCAI'07 Proceedings of the 10th international conference on Medical image computing and computer-assisted intervention - Volume Part I
Blind and semi-blind deblurring of natural images
IEEE Transactions on Image Processing
Variational deblurring of images with uncertain and spatially variant blurs
PR'05 Proceedings of the 27th DAGM conference on Pattern Recognition
IWCIA'04 Proceedings of the 10th international conference on Combinatorial Image Analysis
Blind image restoration by anisotropic regularization
IEEE Transactions on Image Processing
Reconstructing arbitrarily focused images from two differently focused images using linear filters
IEEE Transactions on Image Processing
Space-Variant Restoration of Images Degraded by Camera Motion Blur
IEEE Transactions on Image Processing
Blind and semi-blind deblurring of natural images
IEEE Transactions on Image Processing
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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.