We consider the problem of reconstructing time sequences of spatially sparse signals (with unknown and time-varying sparsity patterns) from a limited number of linear "incohe...
Because more output data must be created than is available from the input, magnification is an ill-posed problem. Traditional magnification relies on resampling an interpolation mo...
We describe a method for automatically and adaptively boosting the visibility of local features in an image. A log intensity image is first decomposed into a set of subbands at mu...
In this contribution we present an algorithm for spatial error concealment of lost image data caused by transmission of images in error prone environments. The surrounding correct...
With the rapid technological advances in machine learning and data mining, it is now possible to train computers with hundreds of semantic concepts for the purpose of annotating i...