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

 

802Electrical EngineeringSouth Kensington Campus

//

Summary

 

Publications

Publication Type
Year
to

159 results found

Frossard P, Dragotti PL, Ortega A, Rabbat M, Ribeiro Aet al., 2017, Introduction to the Cooperative Special Issue on Graph Signal Processing in the IEEE TRANSACTIONS ON SIGNAL AND INFORMATION PROCESSING OVER NETWORKS and the IEEE JOURNAL OF SELECTED TOPICS IN SIGNAL PROCESSING, IEEE JOURNAL OF SELECTED TOPICS IN SIGNAL PROCESSING, Vol: 11, Pages: 771-773, ISSN: 1932-4553

JOURNAL ARTICLE

Frossard P, Dragotti PL, Ortega A, Rabbat M, Ribeiro Aet al., 2017, Introduction to the COOPERATIVE SPECIAL ISSUE ON GRAPH SIGNAL PROCESSING IN THE IEEE JOURNAL OF SELECTED TOPICS IN SIGNAL PROCESSING AND THE IEEE TRANSACTIONS ON SIGNAL AND INFORMATION PROCESSING OVER NETWORKS, IEEE TRANSACTIONS ON SIGNAL AND INFORMATION PROCESSING OVER NETWORKS, Vol: 3, Pages: 448-450, ISSN: 2373-776X

JOURNAL ARTICLE

Huang, Liu T, Dragotti, Stathakiet al., 2017, SRHRF+: Self-Example Enhanced Single Image Super-Resolution Using Hierarchical Random Forests, Computer Vision and Pattern Recognition Workshops

CONFERENCE PAPER

Kotzagiannidis MS, Dragotti PL, 2017, Splines and Wavelets on Circulant Graphs, Applied and Computational Harmonic Analysis, ISSN: 1096-603X

We present novel families of wavelets and associated filterbanks for the analysis and representation of functions defined on circulant graphs. In this work, we leverage the inherent vanishing moment property of the circulant graph Laplacian operator, and by extension, the e-graph Laplacian, which is established as a parameterization of the former with respect to the degree per node, for the design of vertex-localized and critically-sampled higher-order graph (e-)spline wavelet filterbanks, which can reproduce and annihilate classes of (exponential) polynomial signals on circulant graphs. In addition, we discuss similarities and analogies of the detected properties and resulting constructions with splines and spline wavelets in the Euclidean domain. Ultimately, we consider generalizations to arbitrary graphs in the form of graph approximations, with focus on graph product decompositions. In particular, we proceed to show how the use of graph products facilitates a multi-dimensional extension of the proposed constructions and properties.

JOURNAL ARTICLE

Kotzagiannidis MS, Dragotti PL, 2017, Sampling and reconstruction of sparse signals on circulant graphs – an introduction to graph-FRI, Applied and Computational Harmonic Analysis, ISSN: 1096-603X

With the objective of employing graphs toward a more generalized theory of signal processing, we present a novel sampling framework for (wavelet-)sparse signals defined on circulant graphs which extends basic properties of Finite Rate of Innovation (FRI) theory to the graph domain, and can be applied to arbitrary graphs via suitable approximation schemes. At its core, the introduced Graph-FRI-framework states that any K-sparse signal on the vertices of a circulant graph can be perfectly reconstructed from its dimensionality-reduced representation in the graph spectral domain, the Graph Fourier Transform (GFT), of minimum size 2K. By leveraging the recently developed theory of e-splines and e-spline wavelets on graphs, one can decompose this graph spectral transformation into the multiresolution low-pass filtering operation with a graph e-spline filter, with subsequent transformation to the spectral graph domain; this allows to infer a distinct sampling pattern, and, ultimately, the structure of an associated coarsened graph, which preserves essential properties of the original, including circularity and, where applicable, the graph generating set.

JOURNAL ARTICLE

Lu YM, Onativia J, Dragotti PL, 2017, Sparse Representation in Fourier and Local Bases Using ProSparse: A Probabilistic Analysis, IEEE Transactions on Information Theory, Pages: 1-1, ISSN: 0018-9448

JOURNAL ARTICLE

Murray-Bruce J, Dragotti PL, 2017, A Sampling Framework for Solving Physics-Driven Inverse Source Problems, IEEE TRANSACTIONS ON SIGNAL PROCESSING, Vol: 65, Pages: 6365-6380, ISSN: 1053-587X

JOURNAL ARTICLE

Reynolds S, Abrahamsson T, Schuck R, Sjöström PJ, Schultz SR, Dragotti PLet al., 2017, ABLE: An Activity-Based Level Set Segmentation Algorithm for Two-Photon Calcium Imaging Data., eNeuro, Vol: 4

We present an algorithm for detecting the location of cells from two-photon calcium imaging data. In our framework, multiple coupled active contours evolve, guided by a model-based cost function, to identify cell boundaries. An active contour seeks to partition a local region into two subregions, a cell interior and exterior, in which all pixels have maximally "similar" time courses. This simple, local model allows contours to be evolved predominantly independently. When contours are sufficiently close, their evolution is coupled, in a manner that permits overlap. We illustrate the ability of the proposed method to demix overlapping cells on real data. The proposed framework is flexible, incorporating no prior information regarding a cell's morphology or stereotypical temporal activity, which enables the detection of cells with diverse properties. We demonstrate algorithm performance on a challenging mouse in vitro dataset, containing synchronously spiking cells, and a manually labelled mouse in vivo dataset, on which ABLE (the proposed method) achieves a 67.5% success rate.

JOURNAL ARTICLE

Schuck R, Go MA, Garasto S, Reynolds S, Dragotti PL, Schultz Set al., 2017, Multiphoton minimal inertia scanning for fast acquisition of neural activity signals., J Neural Eng

OBJECTIVE: Multi-photon laser scanning microscopy provides a powerful tool for monitoring the spatiotemporal dynamics of neural circuit activity. It is, however, intrinsically a point scanning technique. Standard raster scanning enables imaging at subcellular resolution; however, acquisition rates are limited by the size of the field of view to be scanned. Recently developed scanning strategies such as Travelling Salesman Scanning (TSS) have been developed to maximize cellular sampling rate by scanning only select regions in the field of view corresponding to locations of interest such as somata. However, such strategies are not optimized for the mechanical properties of galvanometric scanners. We thus aimed to develop a new scanning algorithm which produces minimal inertia trajectories, and compare its performance with existing scanning algorithms.
 Approach: We describe here the Adaptive Spiral Scanning (SSA) algorithm, which fits a set of near-circular trajectories to the cellular distribution to avoid inertial drifts of galvanometer position. We compare its performance to raster scanning and TSS in terms of cellular sampling frequency and signal-to-noise ratio (SNR).
 Main Results: Using surrogate neuron spatial position data, we show that SSA acquisition rates
 are an order of magnitude higher than those for raster scanning and generally exceed those achieved by TSS for neural densities comparable with those found in the cortex. We show that this result also holds true for in vitro hippocampal mouse brain slices bath loaded with the synthetic calcium dye Cal-520 AM. The ability of TSS to "park" the laser on each neuron along the scanning trajectory, however, enables higher SNR than SSA when all targets are precisely scanned. Raster scanning has the highest SNR but at a substantial cost in number of cells scanned. To understand the impact of sampling rate and SNR on functional calcium imaging, we used the Crame ́r-Rao Bound on e

JOURNAL ARTICLE

Kotzagiannidis MS, Dragotti PL, 2016, THE GRAPH FRI FRAMEWORK-SPLINE WAVELET THEORY AND SAMPLING ON CIRCULANT GRAPHS, IEEE International Conference on Acoustics, Speech, and Signal Processing, Publisher: IEEE, Pages: 6375-6379, ISSN: 1520-6149

CONFERENCE PAPER

Lawson M, Brookes M, Dragotti PL, 2016, Capturing the plenoptic function in a swipe, Conference on Applications of Digital Image Processing XXXIX, Publisher: SPIE-INT SOC OPTICAL ENGINEERING, ISSN: 0277-786X

CONFERENCE PAPER

Maggioni M, Dragotti PL, 2016, Video Temporal Super-Resolution Using Nonlocal Registration and Self-Similarity, 18th IEEE International Workshop on Multimedia Signal Processing (MMSP), Publisher: IEEE, ISSN: 2163-3517

CONFERENCE PAPER

Murray-Bruce J, Dragotti PL, 2016, Physics-driven quantized consensus for distributed diffusion source estimation using sensor networks, EURASIP JOURNAL ON ADVANCES IN SIGNAL PROCESSING, ISSN: 1687-6180

JOURNAL ARTICLE

Murray-Bruce J, Dragotti PL, 2016, RECONSTRUCTING NON-POINT SOURCES OF DIFFUSION FIELDS USING SENSOR MEASUREMENTS, IEEE International Conference on Acoustics, Speech, and Signal Processing, Publisher: IEEE, Pages: 4004-4008, ISSN: 1520-6149

CONFERENCE PAPER

Murray-Bruce J, Dragotti PL, 2016, SOLVING PHYSICS-DRIVEN INVERSE PROBLEMS VIA STRUCTURED LEAST SQUARES, 24th European Signal Processing Conference (EUSIPCO), Publisher: IEEE, Pages: 331-335, ISSN: 2076-1465

CONFERENCE PAPER

Murray-Bruce J, Dragotti PL, 2016, Solving Inverse Source Problems for linear PDEs using Sparse Sensor Measurements, 50th Asilomar Conference on Signals, Systems, and Computers (ASILOMARSSC), Publisher: IEEE COMPUTER SOC, Pages: 517-521, ISSN: 1058-6393

CONFERENCE PAPER

Onativia J, Lu YM, Dragotti PL, 2016, PROSPARSE DENOISE: PRONY'S BASED SPARSE PATTERN RECOVERY IN THE PRESENCE OF NOISE, IEEE International Conference on Acoustics, Speech, and Signal Processing, Publisher: IEEE, Pages: 4084-4088, ISSN: 1520-6149

CONFERENCE PAPER

Reynolds S, Copeland CS, Schultz SR, Dragotti PLet al., 2016, AN EXTENSION OF THE FRI FRAMEWORK FOR CALCIUM TRANSIENT DETECTION, IEEE 13th International Symposium on Biomedical Imaging (ISBI), Publisher: IEEE, Pages: 676-679, ISSN: 1945-7928

CONFERENCE PAPER

Tagliasacchi M, Visentini-Scarzanella M, Dragotti PL, Tubaro Set al., 2016, Identification of Transform Coding Chains, IEEE TRANSACTIONS ON IMAGE PROCESSING, Vol: 25, Pages: 1109-1123, ISSN: 1057-7149

JOURNAL ARTICLE

Wei X, Dragotti PL, 2016, FRESH-FRI-Based Single-Image Super-Resolution Algorithm, IEEE TRANSACTIONS ON IMAGE PROCESSING, Vol: 25, Pages: 3723-3735, ISSN: 1057-7149

JOURNAL ARTICLE

Zhang Y, Dragotti PL, 2016, Sampling Streams of Pulses With Unknown Shapes, IEEE TRANSACTIONS ON SIGNAL PROCESSING, Vol: 64, Pages: 5450-5465, ISSN: 1053-587X

JOURNAL ARTICLE

Kotzagiannidis MS, Dragotti PL, 2015, Higher-order graph wavelets and sparsity on circulant graphs, Conference on Wavelets and Sparsity XVI, Publisher: SPIE-INT SOC OPTICAL ENGINEERING, ISSN: 0277-786X

CONFERENCE PAPER

Murray-Bruce J, Dragotti PL, 2015, Estimating Localized Sources of Diffusion Fields Using Spatiotemporal Sensor Measurements, IEEE TRANSACTIONS ON SIGNAL PROCESSING, Vol: 63, Pages: 3018-3031, ISSN: 1053-587X

JOURNAL ARTICLE

Murray-Bruce J, Dragotti PL, 2015, CONSENSUS FOR THE DISTRIBUTED ESTIMATION OF POINT DIFFUSION SOURCES IN SENSOR NETWORKS, 40th IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Publisher: IEEE, Pages: 3262-3266, ISSN: 1520-6149

CONFERENCE PAPER

Onativia J, Dragotti PL, 2015, Sparse sampling: theory, methods and an application in neuroscience, BIOLOGICAL CYBERNETICS, Vol: 109, Pages: 125-139, ISSN: 0340-1200

JOURNAL ARTICLE

Onativia J, Lu YM, Dragotti PL, 2015, SPARSITY PATTERN RECOVERY USING FRI METHODS, 40th IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Publisher: IEEE, Pages: 5967-5971, ISSN: 1520-6149

CONFERENCE PAPER

Reynolds S, Onativia J, Copeland CS, Schultz SR, Dragotti PLet al., 2015, Spike Detection Using FRI Methods and Protein Calcium Sensors: Performance Analysis and Comparisons, International Conference on Sampling Theory and Applications (SampTA), Publisher: IEEE, Pages: 533-537

CONFERENCE PAPER

Thongkamwitoon T, Muammar H, Dragotti P-L, 2015, An Image Recapture Detection Algorithm Based on Learning Dictionaries of Edge Profiles, IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY, Vol: 10, Pages: 953-968, ISSN: 1556-6013

JOURNAL ARTICLE

Wei X, Dragotti PL, 2015, Guaranteed Performance in the FRI Setting, IEEE SIGNAL PROCESSING LETTERS, Vol: 22, Pages: 1661-1665, ISSN: 1070-9908

JOURNAL ARTICLE

Wei X, Dragotti PL, 2015, SAMPLING PIECEWISE SMOOTH SIGNALS AND ITS APPLICATION TO IMAGE UP-SAMPLING, IEEE International Conference on Image Processing (ICIP), Publisher: IEEE, Pages: 4293-4297, ISSN: 1522-4880

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: respub-action=search.html&id=00365150&limit=30&person=true