Recovering a signal from auto-correlations or, equivalently, retrieving the phase linked to given Fourier modulus, is wide-spread problem in imaging. This has been tackled number of experimental situations, optical microscopy adaptive astronomy, making use assumptions based on constraints and prior information about recovered object. In similar fashion, deconvolution another common imaging, par...

Recently, deep convolutional neural network (CNN) has achieved great success for image restoration (IR) and provided hierarchical features at the same time. However, most CNN based IR models do not make full use of from original low-quality images; thereby, resulting in relatively-low performance. In this work, we propose a novel efficient residual dense (RDN) to address problem IR, by making b...

Motion blur is a smearing of the image due to a long aperture time. We show that when two motion-blurred images are available, having different blur directions, image restoration can be improved substantially. In particular, the direction of the motion blur and the PSF (Point Spread Function) of the blur can be computed robustly. 2004 Published by Elsevier B.V.