Professor Pier Luigi Dragotti

2024

• Di You and P.L. Dragotti,"INDIGO+: A Unified INN-Guided Probabilistic Diffusion Algorithm for Blind and Non-Blind Image Restoration", IEEE Journal of Selected Topics in Signal Processing, 2024 (open access). GitHub link to code (here)
• P. Song et al.,"Model-Based Explainable Deep Learning for Light-Field Microscopy Imaging", IEEE Transactions on Image Processing, 2024.

2023

• S. Liu, V. Leung, and P.L. Dragotti,"First-spike coding promotes accurate and efficient spiking neural networks for discrete events with rich temporal structures ", Frontiers in Neuroscience. (code available here and here).
  
• V. Leung, J. Huang, Y. Eldar and P.L. Dragotti,"Learning-based Reconstruction of FRI Signals", IEEE Transactions on Signal Processing, 2023. (code here).
  
• Y. Su et al. "A Fast Automatic Method for Deconvoluting Macro X-ray Fluorescence Data Collected from Easel Painting", IEEE Transactions on Computational Imaging, 2023.(code here).
  
• S. Liu and P.L. Dragotti, "Sensing Diversity and Sparsity Models for Event Generation and Video Reconstruction from Events", IEEE Transactions on Pattern Analysis and Machine Intelligence, 2023 (code here).
• H. Verinaz et al. "Physics-based Deep Learning for Imaging Neuronal Activity via Two-photon and Light Field Microscopy", IEEE Transactions on Computational Imaging, 2023.
  

2022

• J.J. Huang and P.L. Dragotti, "WINNet: Wavelet-inspired invertible network for image denoising", IEEE Transactions on Image Processing, 2022 (open access), GitHub code
  
• W.Pu et al. "Mixed X-Ray Image Separation for Artworks With Concealed Designs", IEEE Transactions on Image Processing, 2022
• P. Song et al."Light-field Microscopy for optical imaging of neural activity: when model-based methods meet data-driven approaches" IEEE Signal Processing Magazine, vol 39 March 2022
• H. Verinaz-Jadan et al." Shift-Invariant-Subspace Discretization and Volume Reconstruction for Light Field Microscopy", IEEE Transactions on Computational Imaging, 2022
  

2021

• R. Alexandru, T. Blu and P.L. Dragotti, "Diffusion SLAM: Localising diffusion sources from samples taken by location-unaware mobile sensors", IEEE Transactions on Signal Processing, 2021
  
• N. Perez-Nieves et al., "Neural heterogeneity promotes robust learning", Nature Communications, 2021
  
• Y. Su et al. "When de Prony met Leonardo: An automatic algorithm for chemical element extraction from macro X-Ray Fluorescence Data", IEEE Transactions on Computational Imaging, vol.7, 2021.
  
• X.Deng and P.L. Dragotti, Deep Convolutional Neural Network for Multi-modal Image Restoration and Fusion, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.43 (10), October 2021. GitHub link to code
  
• E. Erdemir, P. L. Dragotti and D. Gunduz, Privacy-aware time-series data sharing with deep reinforcement learning, IEEE Transactions on Information Forensics and Security, vol. 16, pp. 389-401, 2021.‌

2020

• J. Huang and P.L. Dragotti, Learning Deep Analysis Dictionaries for Image Super-Resolution, IEEE Transactions on Signal Processing, vol. 68, pages: 6633 - 6648, 2020
  
• P. Song P, H. Verinaz Jadan, C. Howe, P. Quicke, A. Foust and P.L. Dragotti, 3D localization for light-field microscopy via convolutional sparse coding on epipolar images, IEEE Transactions on Computational Imaging, Vol:6, pages:1017-1032, 2020.
  
• R. Alexandru and P.L. Dragotti, Reconstructing classes of non-bandlimited signals from time encoded information, IEEE Transactions on Signal Processing, pp. 747-763, vol. 68,  2020
  
• X. Deng and P.L. Dragotti, Deep Coupled ISTA Network for Multi-modal Image Super-Resolution, IEEE Transactions on Image Processing, pp 1683-1698, vol.29,  2020. Software code
• X.Deng et al. RADAR: Robust Algorithm for Depth Image Super Resolution Based on FRI Theory and Multimodal Dictionary Learning, IEEE Transactions on Circuits and Systems for Video Technology,vol 30 (8),pp. 2447-2462, August 2020
• P. Song, X. Deng et al., Multimodal Image Super-Resolution via Joint Sparse Representations induced by Coupled Dictionaries, IEEE Trans. on Computational Imaging, vol.6, pp. 57-72, 2020

2019

• M. Lawson, M. Brookes and P.L. Dragotti, Scene Estimation from a Swiped Image, IEEE Trans. on Computational Imaging, vol.5 (4), pp. 540-555, December 2019

2018

• J. Huang and P.L. Dragotti, Photo Realistic Image Completion via Dense Correspondence, IEEE Trans. on Image Processing, vol 27 (11), pp. 5234-5247, November 2018
• S.Reynolds, T. Abrahamsson,J. Sjostrom, S.Schultz and P.L. Dragotti, CosMIC: A Consistent Metric for Spike Inference from Calcium Imaging, Neural Computation, October 2018
  
• G. Yang, S. Yu, H. Dong, G. Slabaugh, P.L. Dragotti, S. Arridge, J. Keegan, Y. Guo, D. Firmin, DAGAN: Deep De-Aliasing Generative Adversarial Networks for Fast Compressed Sensing MRI Reconstruction, IEEE Transactions on Medical Imaging, Vol 37, (6), June 2018
  
• Y. Lu, J. Onativia and P. L. Dragotti, Sparse Representation in Fourier and Local Bases Using ProSparse: A probabilistic Analysis, IEEE Trans on Information Theory, 64(4), pp. 2639-2647, April 2018
• R. Schuck, M.A. Go, S. Garasto, S. Reynolds, P.L. Dragotti and S. R Schultz, Multiphoton minimal inertia scanning for fast acquisition of neural activity signals.  Journal of Neural Engineering, 15, February 2018 (open access).

2017

• J. Murray-Bruce and P.L. Dragotti, A Sampling Framework for Solving Physics-driven Inverse Source Problems, IEEE Trans. on Signal Processing, Vol. 65(24), pp. 6365-6380, December 2017 (open access).
• S.Reynolds et al. ABLE: An Activity-Based Level Set Segmentation Algorithm for Two-Photon Calcium Imaging Data, (open access), eNeuro, October 2017 . Code available here, The ABLE algorithm in action. 
• M. Kotzagiannidis and P.L.Dragotti, Sampling and reconstruction of sparse signals on circulant graphs – an introduction to graph-FRI, Applied and Computational Harmonic Analysis, October 2017
• M. Kotzagiannidis and P.L.Dragotti, Splines and Wavelets on circulant graphs, Applied and Computational Harmonic Analysis, October 2017

2016

• Y. Zhang and P.L. Dragotti, Sampling streams of pulses with unknown shape, IEEE Trans. on Signal Processing,vol. 64(20), pp.5450-5465, October 2016.
  
• X. Wei and P. L. Dragotti, FRESH -FRI-based single image super-resolution algorithm, IEEE Trans on Image Processing, Vol.25(8), pp. 3723-3735, August 2016.
• M. Tagliasacchi, M. Visentini-Scarzanella, P.L. Dragotti and S. Tubaro, Identification of Transform Coding Chains, IEEE Transactions on Image Processing, vol.25(3), March 2016
  
• J. Murray-Bruce and P.L. Dragotti, Physics-driven quantized consensus for distributed diffusion source estimation using sensor networks, EURASIP Journal on Advances in Signal Processing, vol. 2016(14), February 2016 (open access)

2015

• X. Wei and P.L. Dragotti, Guaranteed Performance in the FRI setting, IEEE Signal Processing Letters, Vol:22, Issue 10, pages:1661-1665,October 2015
  
• Zhang Y, Dragotti P.L., 2015. On the reconstruction of wavelet-sparse signals from partial Fourier information. IEEE Signal Processing Letters, Vol:22, Issue 9, Pages:1234-1238, September 2015. [Supplementary information.]
• J. Murray-Bruce and P.L. Dragotti, Estimating localized sources of diffusion fields using spatiotemporal sensor measurements, IEEE Transactions on Signal Processing, vol. 63(12), pp. 3018-3031, June 2015,  (open access)
• T. Thongkamwitoon, H. Muammar and P. L. Dragotti, An image recapture detection algorithm based on learning dictionaries of edge profiles, IEEE Transactions on Information  Forensics and Security, vol. 10 (5), pp.953-968, May 2015. (Data and Software)
• J. Onativia and P.L. Dragotti, Sparse sampling: theory, methods and an application in neuroscience, Biological Cybernetics: Volume 109, Issue 1 (2015), Page 125-139, February 2015.

2014

• P.L. Dragotti and Y. Lu, On Sparse Representation in Fourier and Local Bases, IEEE Trans. on Information Theory, vol. 60 (12), pp. 7888-7899, December 2014 (open access) (software).
• A. Scholefield and P.L. Dragotti, Quadtree Structured Image Approximation for Denoising and Interpolation, IEEE Transactions on Image Processing, vol. 23, no. 3, pp. 1226-1239, March 2014. (Data and Software)
  
• C. Gilliam, P.L. Dragotti and M. Brookes, On the spectrum of the plenoptic function, IEEE Trans. on Image Processing, Vol. 23(2), pp. 502-516, February 2014.
  
• H. Pan, T. Blu, and P.L. Dragotti,, Sampling Curves With Finite Rate of Innovation, IEEE Trans. on Signal Processing, Vol 62(2), pp.458-471, January 2014.
  

2013

• J.A. Uriguen, T. Blu and P.L. Dragotti, FRI Sampling with Arbitrary Kernels', IEEE Trans. on Signal Processing, Vol 61(21), pp.5310-5323, November 2013.
  
• J. Pearson M. Brookes and P.L. Dragotti, Plenoptic layer-based Modelling for Image Based Rendering, IEEE Trans. on Image Processing, Vol.22(9), pp.3405-3419, September 2013.
• J.Onativia, S. Schultz and P.L. Dragotti, A finite rate of innovation algorithm for fast and accurate spike detection from two-photon calcium imaging, Journal of Neural Engineering, 10 (4), August 2013. (Data and Software)

2011-12

• A. Gelman, P.L. Dragotti and V. Velisavljevic, Multiview Image Coding using Depth Layers and an Optimized Bit Allocation, IEEE Trans. on Image Processing, Vol.21(9), pp. 4092-4105, September 2012. (Data and Software)
  
• A. Gelman, P.L. Dragotti and J.Berent, Layer-Based Sparse Representation of Multiview Images, Eurasip Journal on Advances in Signal Processing, March 2012.
  
• V. Chaisintthop and P.L. Dragotti, Centralized and Distributed Semi-parametric Compression of Piecewise Smooth Function, IEEE Trans. on Signal Processing, Vol. 59(7), pp. 3071-3085, July 2011.
• H. Akhondi and P.L. Dragotti, Multichannel Sampling of Multidimensional Parametric Signals,  Sampling Theory in Signal and Image Processing, Vol.10 (1-2), pp.37-57, 2011, ISSN: 1530-6429.

2009-10

• H. Akhondi Asl, P.L. Dragotti and L. Baboulaz, Multichannel Sampling of Signals with Finite Rate of Innovation, IEEE Signal Processing Letter, Vol. 17(8), pp.762-765, August 2010. 
• J. Berent, P.L. Dragotti and T. Blu, Sampling Piecewise Sinusoidal Signals with Finite Rate of Innovation Methods, IEEE Trans. on Signal Processing, Vol. 58(2),pp. 613-625, February 2010.
• N.Gehrig and P.L. Dragotti, Geometry-Driven Distributed Compression of the Plenoptic Function: Performance Bounds and Constructive Algorithms, IEEE Trans. on Image Processing, Vol. 18(3), pp.457-470, March 2009.
• L. Baboulaz and P.L. Dragotti,  Exact Feature Extraction using Finite Rate of Innovation Principles with an Application to Image Super-resolution, IEEE Transactions on Image Processing, Vol. 18(2), pp. 281-298, February 2009. (Data and Software).

2007-08

• T. Blu, P.L. Dragotti, M. Vetterli, P. Marziliano and L. Coulot,  Sparse Sampling of Signal Innovations: Theory, Algorithms and Performance Bounds, IEEE Signal Processing Magazine,  vol. 25 (2), pp. 31-40, March 2008.
• J. Berent and P.L. Dragotti, Plenoptic Manifolds: Exploiting Structure and Coherence in Multiview Images, IEEE Signal Processing Magazine, vol. 24 (6), pp.34-44, November 2007.
• P. Shukla and P.L. Dragotti, ,  Sampling Schemes for Multidimensional Signals with Finite Rate of Innovation, IEEE Trans. on Signal Processing, vol. 55 (7),  pp. 3670-3686, July 2007
• P.L. Dragotti, M. Vetterli and T. Blu,  Sampling Moments and Reconstructing Signals of Finite Rate of Innovation: Shannon meets Strang-Fix, IEEE Trans. on Signal Processing, vol.55 (5), pp. 1741-1757, May 2007.

2006 and before

• M. Gastpar, P.L. Dragotti and M. Vetterli,   The Distributed Karhunen-Loève Transform, IEEE Trans. on Information Theory, vol.52 (12), pp. 5177-5196, December  2006.
• M.Gastpar, M. Vetterli and P.L. Dragotti,  Sensing Reality and Communicating Bits: A Dangerous Liaison , IEEE Signal Processing Magazine, vol.23(4), pp.70-83, July 2006.
• V. Velisavljevic, B. Beferull-Lozano, M. Vetterli and P.L. Dragotti,  Directionlets: Anisotropic multi-directional representation with separable filtering, IEEE Trans. on Image Proc., vol .15(7), pp.1916-1933, July 2006.
• R. Shukla, P.L. Dragotti, M.N. Do and M. Vetterli, Rate-distortion optimized tree structured compression algorithms for piecewise polynomial images, IEEE Trans. on Image Processing, vol. 14(3), pp. 343-359, March 2005.
• N. Gehrig and P.L. Dragotti, Symmetric and Asymmetric Slepian-Wolf codes with systematic and non-systematic linear codes, IEEE Communications Letters, vol. 9 (1), pp. 61-63, January 2005.
• P.L. Dragotti and M. Vetterli, Wavelet Footprints: Theory, Algorithms and Applications, IEEE Trans. on Signal Processing, vol. 51(5), pp. 1306-1323, May 2003. 
• P.L. Dragotti, S. Servetto and M. Vetterli, Filter Banks for Multiple Description Coding: Analysis and Synthesis, IEEE Trans. on Information Theory, vol. 48(7), pp. 2036-2052, July 2002. 
• J. Kovacevic, P. L. Dragotti and V. K Goyal, Filter Bank Frame Expansions with Erasures, IEEE Trans. on Information. Theory, special issue in Honor of Aaron D. Wyner, vol. 48(6), pp. 1439-1450, June 2002.
• P. L. Dragotti, G. Poggi and A.R.P. Ragozini, Compression of Multispectral Images by three-dimensional SPIHT Algorithm, IEEE Trans. Geosci. Remote Sensing, vol.38(1), pp. 416-428, January 2000.