Minh Do

Description

Address

Biography

Minh N. Do is an Assistant Professor in the Department of Electrical and Computer Engineering at the University of Illinois and a part-time faculty member in the Image Formation and Processing group at the Beckman Institute. He received his Doctor of Science degree in Communication Systems from the Swiss Federal Institute of Technology, Lausanne, Switzerland, in 2001. His research interests include signal and image processing, wavelet theory and applications, computational harmonic analysis,and visual information representation.

Honors

National Science Foundation CAREER Award (2003); Best Doctoral Thesis Award from the Swiss Federal Institute of Technology Lausanne (2001); University Medal from the University of Canberra, Australia (1997); Silver Medal from the 32nd International Mathematical Olympiad in Sweden (1991).

Research

Minh Do's research interests are in the broad area of signal and image processing. The primary research goal of his research group has been developing new "true" multidimensional tools that can capture geometrical structures that typically are the dominant feature in images and multidimensional data. Geometry has been long considered in mathematics and computer vision. The challenges in exploring geometry in image processing come from the discrete nature of the data, as well as the issues of robustness, efficiency, and speed. Do's group is working on a discrete-space framework for the construction of multiscale geometric image transforms that can be applied to sampled images. By connecting and unifying ideas from harmonic analysis, visual perception, computer vision, and signal processing, Do's group seeks new fruitful interactions between these fields.

Publications

  • 2016
    • Zhang, Y.; Wei, X. S.; Wu, J. X.; Cai, J. F.; Lu, J. B.; Nguyen, V. A.; Do, M. N., Weakly Supervised Fine-Grained Categorization with Part-Based Image Representation. IEEE Transactions on Image Processing 2016, 25, (4), 1713-1725.
  • 2015
    • Nguyen, H. Q.; Do, M. N., Downsampling of Signals on Graphs via Maximum Spanning Trees. IEEE Transactions on Signal Processing 2015, 63, (1), 182-191, DOI:10.1109/Tsp.2014.2369013.

    • Nguyen, V. A.; Lu, J. B.; Zhao, S.; Vu, D. T.; Yang, H. S.; Jones, D. L.; Do, M. N., Item: Immersive Telepresence for Entertainment and Meetings-a Practical Approach. IEEE Journal of Selected Topics in Signal Processing 2015, 9, (3), 546-561, DOI:10.1109/Jstsp.2014.2375819.

    • Nguyen, T. H.; Sridharan, S.; Marcias, V.; Balla, A. K.; Do, M. N.; Popescu, G., Prostate Cancer Diagnosis Using Quantitative Phase Imaging and Machine Learning. Quantitative Phase Imaging 2015, 9336, DOI:ARTN 933619 DOI 10.1117/12.2080321.

    • Nguyen, T. H.; Majeed, H.; Edwards, C. A.; Do, M. N.; Goddard, L. L.; Popescu, G., Halo-Free Quantitative Phase Imaging with Partially Coherent Light. Quantitative Phase Imaging 2015, 9336, DOI:ARTN 93360n DOI 10.1117/12.2080358.

    • Bui, H. Q.; La, C. N. H.; Do, M. N., A Fast Tree-Based Algorithm for Compressed Sensing with Sparse-Tree Prior. Signal Processing 2015, 108, 628-641.
    • Wang, L. B.; Tang, D.; Guo, Y. W.; Do, M. N., Common Visual Pattern Discovery Via Nonlinear Mean Shift Clustering. IEEE Transactions on Image Processing 2015, 24, (12), 5442-5454.
  • 2014
    • Nguyen, V. A.; Lu, J. B.; Zhao, S. K.; Jones, D. L.; Do, M. N., Teleimmersive Audio-Visual Communication Using Commodity Hardware. IEEE Signal Processing Magazine 2014, 31, (6),
      118-+, DOI:10.1109/Msp.2014.2340232.

    • Babacan, S. D.; Nakajima, S.; Do, M. N., Bayesian Group-Sparse Modeling and Variational Inference. IEEE Transactions on Signal Processing 2014, 62, (11), 2906-2921, DOI: 10.1109/tsp.2014.2319775.

    • Ham, B.; Min, D. B.; Oh, C.; Do, M. N.; Sohn, K., Probability-Based Rendering for View Synthesis. IEEE Transactions on Image Processing 2014, 23, (2), 870-884, DOI: 10.1109/tip.2013.2295716.

    • da Costa, A. L. N. T.; Do, M. N., A Retina-Based Perceptually Lossless Limit and a Gaussian Foveation Scheme with Loss Control. IEEE Journal of Selected Topics in Signal Processing 2014, 8, (3), 438-453, DOI:10.1109/Jstsp.2014.2315716.

  • 2013
    • Chidester, B.; Do, M.; IEEE, Assisting the Visually Impaired Using Depth Inference on Mobile Devices Via Stereo Matching, In Electronic Proceedings of the 2013 IEEE International Conference on Multimedia and Expo Workshops. IEEE, New York, 2013.

    • Meyer, G. P.; Do, M. N.; Real-Time 3D Face Modeling with a Commodity Depth Camera, In Electronic Proceedings of the 2013 IEEE International Conference on Multimedia and Expo Workshops. IEEE, New York, 2013.

    • Min, D. B.; Lu, J. B.; Do, M. N., Joint Histogram-Based Cost Aggregation for Stereo Matching. IEEE Transactions on Pattern Analysis and Machine Intelligence 2013, 35, (10), 2539-2545, DOI: 10.1109/tpami.2013.15.

    • Nguyen, H. M.; Peng, X.; Do, M. N.; Liang, Z. P., Denoising Mr Spectroscopic Imaging Data with Low-Rank Approximations. IEEE Transactions on Biomedical Engineering 2013, 60, (1), 78-89.

    • Nguyen, V. A.; Min, D. B.; Do, M. N., Efficient Techniques for Depth Video Compression Using Weighted Mode Filtering. IEEE Transactions on Circuits and Systems for Video Technology 2013, 23, (2), 189-202.

    • Tan, T., D.; Wang, Y.; Nguyen, L. T.; Do, M. N.; Insana, M. F. Complex Shear Modulus Estimation Using Maximum Likelihood Ensemble Filters, 4th International Conference on Biomedical Engineering, Toi, V. V., Toan, N. B., Dang Khoa, T. Q., Lien Phuong, T. H., Eds, Vietnam, 2013, Vol. 40, 313-316.

  • 2012
    • Do, M. N.; Marchand-Maillet, D.; Vetterli, M., On the Bandwidth of the Plenoptic Function. IEEE Transactions on Image Processing 2012, 21, (2), 708-717.

    • Min, D. B.; Lu, J. B.; Do, M. N., Depth Video Enhancement Based on Weighted Mode Filtering. IEEE Transactions on Image Processing 2012, 21, (3), 1176-1190.

    • Mir, M.; Babacan, S. D.; Bednarz, M.; Do, M. N.; Golding, I.; Popescu, G., Visualizing Escherichia Coli Sub-Cellular Structure Using Sparse Deconvolution Spatial Light Interference Microscopy. PLoS One 2012, 7, (6), e38916.

  • 2011
    • Babacan, S. D.; Wang, Z.; Do, M.; Popescu, G., Cell Imaging Beyond the Diffraction Limit Using Sparse Deconvolution Spatial Light Interference Microscopy. Biomedical Optics Express 2011, 2, (7), 1815-1827.

    • Pham, H.; Ding, H. F.; Sobh, N.; Do, M.; Patel, S.; Popescu, G., Off-Axis Quantitative Phase Imaging Processing Using Cuda: Toward Real-Time Applications. Biomedical Optics Express 2011, 2, (7), 1781-1793.

    • Dapore, A. J.; King, M. R.; Harter, J.; Sarwate, S.; Oelze, M. L.; Zagzebski, J. A.; Do, M. N.; Hall, T. J.; O'Brien, W. D., Analysis of Human Fibroadenomas using Three-Dimensional Impedance Maps. IEEE Transactions on Medical Imaging 2011, 30, (6), 1206-1213.

    • Do, M. N.; Nguyen, Q. H.; Nguyen, H. T.; Kubacki, D.; Patel, S. J., Immersive Visual Communication. IEEE Signal Processing Magazine 2011, 28, (1), 58-66.

    • Law, K. L.; Do, M. N., Multidimensional Filter Bank Signal Reconstruction From Multichannel Acquisition. IEEE Transactions on Image Processing 2011, 20, (2), 317-326.

  • 2010
    • Maitre, M.; Do, M. N., Depth and depth-color coding using shape-adaptive wavelets. Journal of Visual Communication and Image Representation 2010, 21, (5-6), 513-522.

    • Do, M. N.; Kim, C. S.; Muller, K.; Tanimoto, M.; Vetro, A., Multi-Camera Imaging, Coding and Innovative Display: Techniques and Systems. Journal of Visual Communication and Image Representation 2010, 21, (5-6), 375-376.

  • 2009
    • Nguyen, H. T.; Do, M. N., Error Analysis for Image-Based Rendering With Depth Information. IEEE Transactions on Image Processing 2009, 18, (4), 703-716.

    • Law, K. L.; Fossum, R. M.; Do, M. N., Generic Invertibility of Multidimensional FIR Filter Banks and MIMO Systems. IEEE Transactions on Signal Processing 2009, 57, (11), 4282-4291.

    • Lin, D.; Huang, X. H.; Nguyen, Q.; Blackburn, J.; Rodrigues, C.; Huang, T.; Do, M. N.; Patel, S. J.; Hwu, W. M. W., The Parallelization of Video Processing From programming models to applications. IEEE Signal Processing Magazine 2009, 26, (6), 103-112.

    • Lu, Y. M.; Do, M. N.; Laugesen, R. S., A Computable Fourier Condition Generating Alias-Free Sampling Lattices. IEEE Transactions on Signal Processing 2009, 57, (5), 1768-1782.

    • Morrison, R. L.; Do, M. N.; Munson, D. C., MCA: A Multichannel Approach to SAR Autofocus. IEEE Transactions on Image Processing 2009, 18, (4), 840-853.

    • Nguyen, H. M.; Sutton, B. P.; Morrison, R. L.; Do, M. N., Joint Estimation and Correction of Geometric Distortions for EPI Functional MRI Using Harmonic Retrieval. IEEE Transactions on Medical Imaging 2009, 28, (3), 423-434.

  • 2008
    • Nguyen, H. T.; Do, M. N., Hybrid filter banks with fractional delays: Minimax design and application to multichannel sampling. IEEE Transactions on Signal Processing 2008, 56, (7), 3180-3190.

    • Lu, Y. M.; Do, M. N., A theory for sampling signals from a union of subspaces. IEEE Transactions on Signal Processing 2008, 56, (6), 2334-2345.

    • Lu, Y. M.; Do, M. N., Sampling signals from a union of subspaces. IEEE Signal Processing Magazine 2008, 25, (2), 41-47.

    • Lu, Y. M.; Do, M. N., A mapping-based design for nonsubsampled hourglass filter banks in arbitrary dimensions. IEEE Transactions on Signal Processing 2008, 56, (4), 1466-1478.

    • Maitre, M.; Shinagawa, Y.; Do, M. N., Wavelet-based joint estimation and encoding of depth-image-based representations for free-viewpoint rendering. IEEE Transactions on Image Processing 2008, 17, (6), 946-957.

  • 2007
    • Morrison, R. L.; Do, M. N.; Munson, D. C., SAR image autofocus by sharpness optimization: A theoretical study. IEEE Transactions on Image Processing 2007, 16, (9), 2309-2321.

    • da Cunha, A. L.; Do, M. N., On two-channel filter banks with directional vanishing moments. IEEE Transactions on Image Processing 2007, 16, (5), 1207-1219.

    • Lu, Y. M.; Do, M. N., Multidimensional directional filter banks and surfacelets. IEEE Transactions on Image Processing 2007, 16, (4), 918-931.

  • 2006
    • Po, D. D. Y.; Do, M. N., Directional multiscale modeling of images using the contourlet transform. IEEE Transactions on Image Processing 2006, 15, (6), 1610-1620.

    • Xu, D.; Do, M. N., On the number of rectangular tilings. IEEE Transactions on Image Processing 2006, 15, (10), 3225-3230.

    • da Cunha, A. L.; Zhou, J. P.; Do, M. N., The nonsubsampled contourlet transform: Theory, design, and applications. IEEE Transactions on Image Processing 2006, 15, (10), 3089-3101.

    • Huang, Y.; Pollak, I.; Do, M. N.; Bouman, C. A., Fast search for best representations in multitree dictionaries. IEEE Transactions on Image Processing 2006, 15, (7), 1779-1793.

    • Zhou, J. P.; Do, M. N., Multidimensional multichannel FIR deconvolution using Grobner bases. IEEE Transactions on Image Processing 2006, 15, (10), 2998-3007.

  • 2004
    • Do, M.N. and Vetterli, M. (2004), "The Contourlet Transform: An Efficient Directional Multiresolution Image Representation,” IEEE Transactions on Image Processing, in press.

    • Shukla, R., Dragotti, P.L., Do, M.N., and Vetterli, M. (2004), "Rate-distortion Optimized Tree Structured Compression Algorithms for Piecewise Smooth Images," IEEE Transactions on Image Processing, in press.

  • 2003
    • Do, M.N. and Vetterli, M. (2003), "Contourlets," in G.V. Welland, ed., Beyond Wavelets, Academic Press, New York.

    • Do, M.N. and Vetterli, M. (2003), "Framing Pyramids," IEEE Transactions on Signal Processing, 51, pp. 2329-2342.

    • Do, M.N. (2003), "Fast Approximation of Kullback-Leibler Distance for Dependence Trees and Hidden Markov Models," IEEE Signal Processing Letters, 10, pp. 115-118.

    • Do, M.N. and Vetterli, M. (2003), "The Finite Ridgelet Transform for Image Representation," IEEE Transactions on Image Processing, 12, pp.16-28.

Press

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