Publications associées à Supersampling

Motif Cut Sparsifiers

Mikhail Kapralov, Mikhail Makarov, Jakab Tardos

A motif is a frequently occurring subgraph of a given directed or undirected graph G (Milo et al.). Motifs capture higher order organizational structure of G beyond edge relationships, and, therefore, have found wide applications such as in graph clusterin ...

IEEE COMPUTER SOC2022

Hessian Splines For Scanning Transmission X-Ray Microscopy

Michaël Unser, Thomas Jean Debarre

Scanning transmission X-ray microscopy (STXM) produces images in which each pixel value is related to the measured attenuation of an X-ray beam. In practice, the location of the illuminated region does not exactly match the desired uniform pixel grid. This ...

IEEE2020

Learning Data Triage: Linear Decoding Works for Compressive MRI

Volkan Cevher, Yen-Huan Li

The standard approach to compressive sampling considers recovering an unknown deterministic signal with certain known structure, and designing the sub-sampling pattern and recovery algorithm based on the known structure. This approach requires looking for ...

Ieee2016

Interior Tomography Using 1D Generalized Total Variation. Part II: Multiscale Implementation

Michaël Unser, John Paul Ward

To address the classic interior tomography problem where projections at each view extend only to the shadow of a circular region completely interior to the subject being scanned, previously we showed that the exact recovery of two- and three-dimensional pi ...

Siam Publications2015

A Fast Hadamard Transform for Signals with Sub-linear Sparsity in the Transform Domain

Martin Vetterli, Robin Scheibler, Saeid Haghighatshoar

In this paper, we design a new iterative low-complexity algorithm for computing the Walsh-Hadamard transform (WHT) of an N dimensional signal with a K-sparse WHT. We suppose that N is a power of two and K = O(N^α), scales sub-linearly in N for some α ∈ (0, ...

Institute of Electrical and Electronics Engineers2015

Jaggies as aliasing or reconstruction phenomena: a tutorial

Roger Hersch, Isaac Amidror

Jaggies (staircasing effects) along slanted lines or curved edges are omnipresent in digital imaging. They are so widespread in digital display devices that very often they are associated with the modern "computerized" world (and sometimes even intentional ...

Is&T & Spie2014

Sampling and Reconstruction of Spatial Fields using Mobile Sensors

Martin Vetterli, Jayakrishnan Unnikrishnan

Spatial sampling is traditionally studied in a static setting where static sensors scattered around space take measurements of the spatial field at their locations. In this paper we study the emerging paradigm of sampling and reconstructing spatial fields ...

Institute of Electrical and Electronics Engineers2013

Sampling and reconstructing diffusion fields in presence of aliasing

Martin Vetterli, Juri Ranieri

The reconstruction of a diffusion field, such as temperature, from samples collected by a sensor network is a classical inverse problem and it is known to be ill-conditioned. Previous work considered source models, such as sparse sources, to regularize the ...

2013

Sampling and reconstructing spatial fields using mobile sensors

Martin Vetterli, Jayakrishnan Unnikrishnan

The classical approach to sampling time-invariant spatial fields uses static sensors distributed over space. We study a new approach involving mobile sensors that move through space measuring the field values along their paths. A single moving sensor can t ...

Ieee2012

Super-Resolution from Unregistered and Totally Aliased Signals Using Subspace Methods

Martin Vetterli, Luciano Sbaiz, Patrick Vandewalle

In many applications, the sampling frequency is limited by the physical characteristics of the components: the pixel pitch, the rate of the A/D converter, etc. A low-pass filter is then often applied before the sampling operation to avoid aliasing. However ...

Institute of Electrical and Electronics Engineers2007