In linear image restoration, the point spread function of the degrading system is assumed known even though this information is usually not available in real applications. As a re...
We formulate the multiframe blind deconvolution problem in an incremental expectation maximization (EM) framework. Beyond deconvolution, we show how to use the same framework to a...
Stefan Harmeling, Suvrit Sra, Michael Hirsch, Bern...
Abstract. Segmentation and blind restoration are both classical problems, that are known to be difficult and have attracted major research efforts. This paper shows that the two pr...
We propose a new image and blur prior model, based on nonstationary autoregressive (AR) models, and use these to blindly deconvolve blurred photographic images, using the Gibbs sa...
In many real applications traditional superresolution methods fail to provide high-resolution images due to objectionable blur and inaccurate registration of input low-resolution ...