Signal & applications Publications

Optimal Transport:

  • F.M. Ngolè Mboula, and J.-L. Starck,  "PSFs field learning based on Optimal Transport distances", submitted, 2016.

Wavelet:

Beyond wavelets: Ridgelet, Curvelet, Dictionary Learning:

Noise Modeling and Denoising:

Poisson noise:

Deconvolution - superresolution:

Blind Source Separation:

  • M. Jiang, J. Bobin and J.-L. Starck, "Joint Multichannel Deconvolution and Blind Source Separation, submitted, 2016

 

Detection:

Compression:

  • N. Barbey, M.Sauvage, J.-L. Starck, and R. Ottensamer, "Feasibility and performances of compressed-sensing and sparse map-making with Herschel/PACS data", Astronomy and Astrophysics, 527, 102 , 2011.
  • J.-L. Starck and J. Bobin, "Astronomical Data Analysis and Sparsity: from Wavelets to Compressed Sensing" , Proceedings of the IEEE Special Issue on: Applications of Sparse Representation and Compressive Sensing, Vol. 98, No. 6, pp 1021-1030, 2010.
  • J. Bobin, J.-L. Starck, and R. Ottensamer, "Compressed Sensing in Astronomy" , IEEE Journal of Selected Topics in Signal Processing , Vol 2, no 5, pp 718--726, 2008.
  • F. Murtagh, M. Louys, J.-L. Starck, F. Bonnarel and M. Farid, "Compression of grayscale scientific and medical images - principles, environments, evaluation", IEE Electronics and Communication Engineering Journal, 1, 1, pp 111-127, 2002.
  • M. Farid, F. Murtagh and J.L. Starck, "Computer display control and interaction using eye-gaze" , Journal of the Society for Information Display, Vol 10, No 3, pp 289-29, 2002.
  • F. Murtagh, M. Louys, J.L. Starck and F. Bonnarel, "Compression of grayscale scientific and medical image data", CODATA Data Science Journal, 1, 111-127, 2002. Available at: "www.datasciencejournal.org" .
  • M. Louys, J.L. Starck, S. Mei, F. Bonnarel, and F. Murtagh, "Astronomical Image Compression", Astronomy and Astrophysics Suppl. Ser. 136, 579-590 , 1999.
  • M. Louys, J.L. Starck and F. Murtagh, "Lossless Compression of Astronomical Images", Irish Astronomical Journal , Vol 26, pp 119-120, 1999.
  • F. Murtagh, J.-L. Starck and M. Louys, "Very high quality image compression based on noise modeling", International Journal of Imaging Systems and Technology, 9, 38-45, 1998.
  • Starck, J.-L., Murtagh, F., Pirenne, B. and Albrecht, M., "Astronomical image compression based on noise suppression" , Publications of the Astronomical Society of the Pacific, 108, 446-455, 1996.
  • J.L. Starck, F. Murtagh, and M. Louys, "High Quality Astronomical Image Compression", Vistas in Astronomoy, Vol. 41, No. 3, pp 439-446, 1997.
  • J.L. Starck, F. Murtagh, and D. Durand, "New Result in Astronomical Image Compression", NASA Science Information Systems Newsletter, Vol. II, 1996, Issue 39. 

Texture analysis:

Segmentation/clustering:

Compressed Sensing:

Morphological Diversity:

Inpainting:

Multi/Hyper-spectral Data:

Data on the Sphere :

Time Series: financial data and electricity load times series forecasting and filtering 

  • F. Murtagh, J.-L. Starck and O. Renaud, "On Neuro-Wavelet Modeling" , Decision Support Systems Journal, 37, 475-484, 2004.
  • O. Renaud, J.L. Starck and F. Murtagh, "Prediction based on a Multiscale Decomposition", International Journal of Wavelets, Multiresolution and Information Processing (IJWMIP), Vol. 1, No. 2, 217-232, 2003.
  • G. Zheng, J.L. Starck, J.G. Campbell and F. Murtagh, "Multiscale transforms for filtering financial data streams", Journal of Computational Intelligence in Finance, 7, 18-35, 1999. Paper available online.

Application in Medical Imaging and Bioimaging:

Application in Agriculture:

  • M. Morehart, F. Murtagh and J.L. Starck, "Spatial representation of economic and financial measures used in agriculture via wavelet analysis", International Journal of Geographic Information Systems, 13, 557-576, 1999.

Application in Video Processing :

Spectral Analysis:

Entropy:

Range Imaging:

  • G. Tsagkatakis, A. Woiselle, G. Tzagkarakis, M. Bousquet, J. L. Starck, and P. Tsakalides, “Multireturn Compressed Gated Range Imaging,” Optical Engineering, special issue on Computational Approaches to Imaging LADAR, 031106, 2015. doi:10.1117/1.OE.54.3.031106.