FAST FILTERING

"Fast Filtering for Computer Graphics, Vision and Computational Sciences"

 Coordinatore THE HEBREW UNIVERSITY OF JERUSALEM. 

Spiacenti, non ci sono informazioni su questo coordinatore. Contattare Fabio per maggiori infomrazioni, grazie.

 Nazionalità Coordinatore Israel [IL]
 Totale costo 1˙320˙200 €
 EC contributo 1˙320˙200 €
 Programma FP7-IDEAS-ERC
Specific programme: "Ideas" implementing the Seventh Framework Programme of the European Community for research, technological development and demonstration activities (2007 to 2013)
 Code Call ERC-2013-StG
 Funding Scheme ERC-SG
 Anno di inizio 2013
 Periodo (anno-mese-giorno) 2013-08-01   -   2018-07-31

 Partecipanti

# participant  country  role  EC contrib. [€] 
1    THE HEBREW UNIVERSITY OF JERUSALEM.

 Organization address address: GIVAT RAM CAMPUS
city: JERUSALEM
postcode: 91904

contact info
Titolo: Ms.
Nome: Hani
Cognome: Ben-Yehuda
Email: send email
Telefono: +972 2 6586676
Fax: +972 7 22447007

IL (JERUSALEM) hostInstitution 1˙320˙200.00
2    THE HEBREW UNIVERSITY OF JERUSALEM.

 Organization address address: GIVAT RAM CAMPUS
city: JERUSALEM
postcode: 91904

contact info
Titolo: Prof.
Nome: Raanan
Cognome: Fattal
Email: send email
Telefono: +972 2 5494554
Fax: +972 2 5494554

IL (JERUSALEM) hostInstitution 1˙320˙200.00

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connection    ideas    explicit    time    operations    image    domain    filtering    filters       varying    lti    multiscale    equations    convolution    matrix    implicit    linear    deriving    multigrid    preconditioning   

 Obiettivo del progetto (Objective)

'The world of digital signal processing, in particular computer graphics, vision and image processing, use linear and non-linear, explicit and implicit filtering extensively to analyze, process and synthesize images. Given nowadays high-resolution sensors, these operations are often very time consuming and are limited to devices with high-CPU power.

Traditional linear translation-invariant (LTI) transformations, executed using convolution, requires O(N^2) operations. This can be lowered to O(N log N) via FFT over suitable domains. There are very few sets of filters to which optimal, linear-time, procedures are known. This situation is more complicated in the newly-emerging domain of non-linear spatially-varying filters. Exact application of such filter requires O(N^2) operations and acceleration methods involve higher space dimension introducing severe memory cost and truncation errors.

In this research proposal we intend to derive fast, linear-time, procedures for different types of LTI filters by exploiting a deep connection between convolution, spatially-homogeneous elliptic equations and the multigrid method for solving such equations. Based on this circular connection we draw novel prospects for deriving new multiscale filtering procedures.

A second part of this research proposal is devoted to deriving efficient explicit and implicit non-linear spatially-varying edge-aware filters. One front consists of the derivation of novel multi-level image decomposition that mimics the action of inhomogeneous diffusion operators. The idea here is, once again, to bridge the gap with numerical analysis and use ideas from multiscale matrix preconditioning for the design of new biorthogonal second-generation wavelets.

Moreover, this proposal outlines a new multiscale preconditioning paradigm combining ideas from algebraic multigrid and combinatorial matrix preconditioning. This intermediate approach offers new ways for overcoming fundamental shortcomings in this domain.'

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