Imperial College London

ProfessorPier LuigiDragotti

Faculty of EngineeringDepartment of Electrical and Electronic Engineering

Professor of Signal Processing
 
 
 
//

Contact

 

+44 (0)20 7594 6192p.dragotti

 
 
//

Location

 

814Electrical EngineeringSouth Kensington Campus

//

Summary

 

Publications

Publication Type
Year
to

255 results found

Wang Y, Brookes M, Dragotti PL, 2008, OBJECT RECOGNITION USING MULTI-VIEW IMAGING, 9th International Conference on Signal Processing, Publisher: IEEE, Pages: 810-813

Conference paper

Vandewalle P, Baboulaz L, Dragotti PL, Vetterli Met al., 2008, SUBSPACE-BASED METHODS FOR IMAGE REGISTRATION AND SUPER-RESOLUTION, 15th IEEE International Conference on Image Processing (ICIP 2008), Publisher: IEEE, Pages: 645-648, ISSN: 1522-4880

Conference paper

Berent J, Dragotti PL, 2007, Plenoptic manifolds, IEEE SIGNAL PROCESSING MAGAZINE, Vol: 24, Pages: 34-44, ISSN: 1053-5888

Journal article

Berent J, Dragotti PL, 2007, Plenoptic Manifolds: Exploiting Structure and Coherence in Multi-View Images, IEEE Signal Processing Magazine, Vol: 24, Pages: 34-44

Journal article

Chaisinthop V, Dragotti PL, 2007, A new approach to distributed video coding using sampling of signals with finite rate of innovation

Conference paper

Gastpar M, Dragotti PL, Vetterli M, 2007, The distributed Karhunen-Loeve transform (vol 52, pg 5177, 2006), IEEE TRANSACTIONS ON INFORMATION THEORY, Vol: 53, Pages: 4400-4400, ISSN: 0018-9448

Journal article

Berent J, Dragotti PL, 2007, Unsupervised Extraction of Coherent Regions for Image Based Rendering, British Machine Vision Conference (BMVC)

Conference paper

Baboulaz L, Dragotti PL, 2007, Local Feature Extraction for Image Super-Resolution, IEEE International Conference on Image Processing (ICIP)

Conference paper

Gehrig N, Dragotti PL, 2007, Distributed Compression of Multi-View Images using a Geometric Approach, IEEE International Conference on Image Processing (ICIP)

Conference paper

Velisavljevic V, Beferull-Lozano B, Vetterli M, Dragotti PLet al., 2007, Image representation and compression using directionlets, Conference on Wavelet Applications in Signal and Image Processing, Wavelets XII

Conference paper

Chaisinthop V, Dragotti PL, 2007, Distributed Video Coding based on Sampling of Signals with Finite Rate of Innovation, Conference on Wavelet Applications in Signal and Image Processing, Wavelets XI

Conference paper

Shukla P, Dragotti PL, 2007, Sampling schemes for multidimensional signals with finite rate of innovation, IEEE International Conference on Image Processing (ICIP 2006), Pages: 3670-3686

In this paper, we consider the problem of sampling signals that are nonband-limited but have finite number of degrees of freedom per unit of time and call this number the rate of innovation. Streams of Diracs and piecewise polynomials are the examples of such signals, and thus are known as signals with finite rate of innovation (FRI). We know that the classical ("band-limited sinc") sampling theory does not enable perfect reconstruction of such signals from their samples since they are not band-limited. However, the recent results on FRI sampling suggest that it is possible to sample and perfectly reconstruct such nonband-limited signals using a rich class of kernels. In this paper, we extend those results in higher dimensions using compactly supported kernels that reproduce polynomials (satisfy Strang-Fix conditions). In fact,the polynomial reproduction property of the kernel makes it possible to obtain the continuous moments of the signal from its samples. Using these moments and the annihilating filter method (Prony's method), the innovative part of the signal, and therefore, the signal itself is perfectly reconstructed. In particular, we present local (directional-derivatives-based) and global (complex-moments-based, Radon-transform-based) sampling schemes for classes of FRI signals such as sets of Diracs, bilevel, and planar polygons, quadrature domains (e.g., circles, ellipses, and cardioids), 2-D polynomials with polygonal boundaries, and n-dimensional Diracs and convex polytopes. This work has been explored in a promising way in super-resolution algorithms and distributed compression, and might find its applications in photogrammetry, computer graphics, and machine vision.

Conference paper

Shukla P D, Dragotti P L, 2007, Sampling Schemes for Multidimensional Signals with Finite Rate of Innovation, IEEE Trans. on Signal Processing, Vol: 55, Pages: 3670-3686

Journal article

Dragotti P L, Vetterli M, Blu T, 2007, Sampling moments and reconstructing signals of finite rate of innovation: Shannon meets Strang–Fix, IEEE Trans. on Signal Processing, Vol: 55, Pages: 1741-1757, ISSN: 1053-587X

Journal article

Dalai M, Leonardi R, Dragotti P L, 2007, Distributed Coding of Shifts Using the DFT Phase

Conference paper

Velisavljevic V, Beferull-Lozano B, Vetterli M, Dragotti PLet al., 2007, Image representation and compression using directionlets, Conference on Wavelets XII, Publisher: SPIE-INT SOC OPTICAL ENGINEERING, ISSN: 0277-786X

Conference paper

Chaisinthop V, Dragotti PL, 2007, Distributed video coding based on sampling of signals with finite rate of innovation - art. no. 67011C, Conference on Wavelets XII, Publisher: SPIE-INT SOC OPTICAL ENGINEERING, Pages: C7011-C7011, ISSN: 0277-786X

Conference paper

Gehrig N, Dragotti PL, 2007, Distributed compression of multi-view images using a geometrical coding approach, IEEE International Conference on Image Processing (ICIP 2007), Publisher: IEEE, Pages: 3217-3220, ISSN: 1522-4880

Conference paper

Gastpar M, Dragotti PL, Vetterli M, 2006, The distributed Karhunen-Loeve transform, IEEE Data Compression Conference, Publisher: IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, Pages: 5177-5196, ISSN: 0018-9448

Conference paper

Berent J, Dragotti P J, 2006, Segmentation of Epipolar-Plane Image Volumes with Occlusion and Disocclusion Competition, International Workshop on Multimedia Signal Processing

Conference paper

Shukla P D, Dragotti P L, 2006, Tomographic Approach for Sampling Multidimensional Signals with Finite Rate of Innovation, International Conference on Image Processing (ICIP)

Conference paper

Velisavljevic V, Beferull-Lozano B, Vetterli M, Dragotti P Let al., 2006, Low-Rate Reduced Complexity Image Compression using Directionlets, International Conference on Image Processing (ICIP)

Conference paper

Dragotti P L, Vetterli M, Blu T, 2006, Exact Local Reconstruction Algorithms for Signals with Finite Rate of Innovation, International Conference on Image Processing (ICIP)

Conference paper

Baboulaz L, Dragotti P L, 2006, Distributed Acquisition and Image Super-Resolution Based on Continuous Moments from Samples, International Conference on Image Processing (ICIP)

Conference paper

Velisavljevic V, Beferull-Lozano B, Vetterli M, Dragotti PLet al., 2006, Directionlets: Anisotropic multidirectional representation with separable filtering, IEEE TRANSACTIONS ON IMAGE PROCESSING, Vol: 15, Pages: 1916-1933, ISSN: 1057-7149

Journal article

Gastpar M, Vetterli M, Dragotti PL, 2006, Sensing reality and communicating bits: A dangerous liaison - Is digital communication sufficient for sensor networks?, IEEE SIGNAL PROCESSING MAGAZINE, Vol: 23, Pages: 70-83, ISSN: 1053-5888

Journal article

Berent J, Dragotti PL, 2006, Perfect reconstruction schemes for sampling piecewise sinusoidal signals, 31st IEEE International Conference on Acoustics, Speech and Signal Processing, Publisher: IEEE, Pages: 377-+, ISSN: 1520-6149

Conference paper

Gehrig N, Dragotti PL, 2006, Distributed sampling and compression of scenes with finite rate of innovation in camera sensor networks, Data Compression Conference, Publisher: IEEE COMPUTER SOC, Pages: 83-92, ISSN: 1068-0314

Conference paper

Gastpar M, Vetterli M, Dragotti PL, 2006, Sensing and communication with and without bits, 31st IEEE International Conference on Acoustics, Speech and Signal Processing, Publisher: IEEE, Pages: 1157-+, ISSN: 1520-6149

Conference paper

Berent J, Dragotti PL, 2006, Perfect reconstruction schemes for sampling piecewise sinusoidal signals, 31st IEEE International Conference on Acoustics, Speech and Signal Processing, Publisher: IEEE, Pages: 2828-2831, ISSN: 1520-6149

Conference paper

This data is extracted from the Web of Science and reproduced under a licence from Thomson Reuters. You may not copy or re-distribute this data in whole or in part without the written consent of the Science business of Thomson Reuters.

Request URL: http://wlsprd.imperial.ac.uk:80/respub/WEB-INF/jsp/search-html.jsp Request URI: /respub/WEB-INF/jsp/search-html.jsp Query String: id=00365150&limit=30&person=true&page=7&respub-action=search.html