Filip Šroubek received the M.Sc. degree in computer science from the Czech Technical University, Prague, Czech Republic in 1998 and the Ph.D. degree in computer science from Charles University, Prague, Czech Republic in 2003. From 2004 to 2006, he was on a postdoctoral position in the Instituto de Optica, CSIC, Madrid, Spain. In 2010/2011 he received a Fulbright Visiting Scholarship at the University of California, Santa Cruz. In 2014, he became a research professor in Physico-Mathematical Sciences (Informatics and Cybernetics) at the Czech Academy of Sciences. In 2016, he became an associate professor at the Faculty of Mathematics and Physics, Charles University. Currently he is the deputy head of the Department of Image Processing.
Selected publications:
Molecularly targeted protease-activated probes for visualization of glioblastoma: a comparison with 5-ALA Journal of Neurosurgery [2024] DOI: 10.3171/2024.1.JNS231137
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Blur Invariants for Image Recognition International Journal of Computer Vision vol.131, 9, p. 2298-2315 [2023] DOI: 10.1007/s11263-023-01798-7
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FCHO controls AP2’s initiating role in endocytosis through a PtdIns(4,5)P2-dependent switch> Science Advances vol.8, eabn2018 [2022] DOI: 10.1126/sciadv.abn2018
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Spectral Pre-Adaptation for Restoring Real-World Blurred Images using Standard Deconvolution Methods Image Processing On Line vol.12, 1, p. 218-246 [2022] DOI: 10.5201/ipol.2022.385
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Precise International Roughness Index Calculation
International Journal of Pavement Research and Technology vol.15, 6, p. 1413-1419 [2022] DOI: 10.1007/s42947-021-00097-z
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Blur-Invariant Similarity Measurement of Images IEEE Transactions on Pattern Analysis and Machine Intelligence vol.43, 8, p. 2882-2884 [2021] DOI: 10.1109/TPAMI.2020.3036630
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Tracking by Deblatting International Journal of Computer Vision vol.129, 9, p. 2583-2604 [2021] DOI: 10.1007/s11263-021-01480-w Honorable Mention at GCPR 2019
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Restoration of Fast Moving Objects IEEE Transactions on Image Processing vol.29, 1, p. 8577-8589 [2020] DOI: 10.1109/TIP.2020.3016490
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Image Restoration in Portable Devices: Algorithms and Optimization
Journal of Signal Processing Systems for Signal Image and Video Technology vol.91, 1, p. 9-20 [2019] DOI: 10.1007/s11265-018-1410-7
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A computer-assisted system for handheld whole-breast ultrasonography
International Journal of Computer Assisted Radiology and Surgery vol.14, 3, p. 509-516 [2019] DOI: 10.1007/s11548-018-01909-7
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Blind Deconvolution With Model Discrepancies
IEEE Transactions on Image Processing vol.26, 5, p. 2533-2544 [2017] DOI: 10.1109/TIP.2017.2676981
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Fast convolutional sparse coding using matrix inversion lemma
Digital Signal Processing vol.55, 1, p. 44-51 [2016] DOI: 10.1016/j.dsp.2016.04.012
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Decomposition of Space-Variant Blur in Image Deconvolution
IEEE Signal Processing Letters vol.23, 3, p. 346-350 [2016] DOI: 10.1109/LSP.2016.2519764
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PSF accuracy measure for evaluation of blur estimation algorithms
Proceedings of the 2015 IEEE International Conference on Image Processing, ICIP, p. 2080-2084, [2015] DOI: 10.1109/ICIP.2015.7351167 Top 10% paper
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Image deblurring in smartphone devices using built-in inertial measurement sensors
Journal of Electronic Imaging vol.22, 1 [2013] DOI: 10.1117/1.JEI.22.1.011003
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Blind Deconvolution Using Alternating Maximum a Posteriori Estimation with Heavy-Tailed Priors
Computer Analysis of Images and Patterns, p. 59-66, Computer Analysis of Images and Patterns [2013] Outstanding Contribution Award
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Robust Multichannel Blind Deconvolution via Fast Alternating Minimization
IEEE Transactions on Image Processing vol.21, 4, p. 1687-1700 [2012] DOI: 10.1109/TIP.2011.2175740
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A Unified Approach to Superresolution and Multichannel Blind Deconvolution
IEEE Transactions on Image Processing vol.16, 9, p. 2322-2332 [2007]
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Multichannel blind deconvolution of spatially misaligned images
IEEE Transactions on Image Processing vol.14, 7, p. 874-883 [2005]
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See more information (research activities, highlights, tools) in section Research