10 accepted papers
The reconstruction quality in compressed sensing MRI can be significantly improved by optimizing the k-space sampling. While previous works have mainly focused on total variation and other traditional regularizers, more recent denoising-driven regularizers have not been fully explored. We address th…
Plug-and-Play (PnP) algorithms leverage the power of modern denoisers for image reconstruction. They have been shown to deliver state-of-the-art reconstructions using CNN denoisers. It was established in recent works that convergence of these iterative algorithms can be guaranteed using nonexpansive…
The problem of training a convolutional neural network (CNN) with a stipulated Lipschitz bound comes up in applications such as adversarial robustness, stability of closed-loop controllers, and image reconstruction. The present work was motivated by Plug-and-Play (PnP) and Regularization-by-Denoisin…
Multiband fusion involves combining an image having high spatial and low spectral resolution with another image having low spatial and high spectral resolution—resulting in a single multiband image with high spatial and spectral resolutions. In classical variational techniques, this problem is formu…
We consider the problem of signal reconstruction from linearly corrupted data using plug-and-play (PnP) regularization. As opposed to traditional sparsity-promoting regularizers, PnP uses an off-the-shelf denoiser within a proximal algorithm such as ISTA or ADMM for image reconstruction. Although Pn…
We propose a fast algorithm for an adaptive variant of the classical bilateral filter, where the range kernel is allowed to vary from pixel to pixel. Several fast and accurate algorithms have been proposed for bilateral filtering, but they assume that the same range kernel is used at each pixel and…
Consider a network with N nodes in d dimensions, and M overlapping subsets P <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sub> , ⋯,P <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">M</sub> (subnetwork…
Due to availability of large amounts of multimedia data, cross-modal matching is gaining increasing importance. Hashing based techniques provide an attractive solution to this problem when the data size is large. Different scenarios of cross-modal matching are possible, for example, data from the di…
The Euclidean Median (EM) of a set of points Ω in an Euclidean space is the point x minimizing the (weighted) sum of the Euclidean distances of x to the points in Ω. While there exits no closed-form expression for the EM, it can nevertheless be computed using iterative methods such as the Weiszfeld…
In this paper, we describe an algorithm for sensor network localization (SNL) that proceeds by dividing the whole network into smaller subnetworks, then localizes them in parallel using some fast and accurate algorithm, and finally registers the localized subnetworks in a global coordinate system. W…