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Minh N. Do: Publications

Full Publication List on Google Scholar

Journal Papers | Conference Papers | Others


Journal Papers

  1. S. Liu and M. N. Do, Inverse rendering and relighting from multiple color plus depth images, IEEE Transactions on Image Processing.

  2. S. Kim, D. Min, B. Ham, M. N. Do and K. Sohn, DASC: Robust dense descriptor for multi-modal and multi-spectral correspondence estimation, IEEE Transactions on Pattern Analysis and Machine Intelligence, pp. 1712-1729, Sep. 2017.

  3. J. A. Bengua, H. N. Phien, H. D. Tuan, and M. N. Do, Matrix product state for higher-order tensor compression and classification, IEEE Transactions on Signal Processing.

  4. J. A. Bengua, H. N. Phien, H. D. Tuan, and M. N. Do, Efficient tensor completion for color image and video recovery: Low-rank tensor train, IEEE Transactions on Image Processin, pp. 2466-2479, Feb. 2017.

  5. W.-Y. Lin, F. Wang, M.-M. Cheng, S.-K. Yeung, P. H. S. Torr, M. N. Do, and J. Lu, CODE: Coherence based decision boundaries for feature correspondence, IEEE Transactions on Pattern Analysis and Machine Intelligence.

  6. T. H. Nguyen, S. Sridharan, V. Macias, A. K. Balla, J. Melamed, M. N. Do, and G. Popescu, Automatic Gleason grading of prostate cancer using quantitative phase imaging and machine learning, Journal of Biomedical Optics, 2017.

  7. T. H. Nguyen, M. Kandel, H. M. Shakir, C. B.-Popescu, M. N. Do, and G. Popescu, Halo-free Phase Contrast Microscopy, Scientific Reports, 2017.

  8. A. J. Bower, B. Chidester, J. Li, Y. Zhao, M. Marjanovic, E. J. Chaney, M. N. Do, S. A. Boppart, A quantitative framework for the analysis of multimodal optical microscopy images, Quant Imaging Med Surg, 7(1):24-37, 2017.

  9. R. S. Pahwa, J. Lu, N. Jiang, T. T. Ng, and M. N. Do, Locating 3D object proposals: A depth-based online approach, IEEE Transactions on Circuits and Systems for Video Technology.

  10. Y. Zhang, L. Cheng, J. Wu, J. Cai, M. N. Do, and J. Lu, Action recognition in still images with minimum annotation efforts, IEEE Transactions on Image Processing, vol. 25 (11), 5479-5490, Nov. 2016.

  11. J. Lu, Y. Li, H. Yang, D. Min, W. Eng, and M. N. Do, PatchMatch Filter: Edge-aware filtering meets randomized search for visual correspondence, IEEE Transactions on Pattern Analysis and Machine Intelligence, pp. 1866-1879, Oct. 2016.

  12. Y. Zhang, X. S. Wei, J. Wu, J. Cai, J. Lu, V. A. Nguyen, and M. N. Do, Weakly supervised fine-grained categorization with part-based image representation, IEEE Transactions on Image Processing, vol. 25 (4), 1713-1725, Apr. 2016.

  13. L. Wang, D. Tang, Y. Guo, and M. N. Do, Common visual pattern discovery via nonlinear mean shift clustering, IEEE Transactions on Image Processing, vol. 24, no. 12, pp. 5442-5454, Dec. 2015.

  14. V.-A. Nguyen, J. Lu, S. Zhao, D. T. Vu, H. Yang, D. L. Jones, and M. N. Do, ITEM: Immersive Telepresence for Entertainment and Meetings - A Practical Approach, IEEE Journal of Selected Topics in Signal Processing, vol.9, no.3, pp.546-561, April 2015.

  15. H. Q. Bui, C. N. H. La, and M. N. Do, A fast tree-based algorithm for compressed sensing with sparse-tree prior, Signal Processing, pp. 628-641, vol. 108, Mar. 2015.

  16. H. Q. Nguyen and M. N. Do, Downsampling of signals on graphs via maximum spanning trees, IEEE Transactions on Signal Processing, pp. 182-191, vol. 63, Jan. 2015.

  17. H. Q. Nguyen and M. N. Do, Inverse rendering of Lambertian surfaces using subspace methods, IEEE Transactions on Image Processing, pp. 5545-5558, Dec. 2014.

  18. D. Min, S. Choi, J. Lu, B. Ham, K. Sohn, and M. N. Do, Fast global image smoothing based on weighted least squares, IEEE Transactions on Image Processing, pp. 5638-5653, Dec. 2014.

  19. V. A. Nguyen, J. Lu, S. Zhao, D. L. Jones, and M. N. Do, Teleimmersive audio-visual communication using commodity hardware, IEEE Signal Processing Magazine, Nov. 2014.

  20. S. D. Babacan, S. Nakajima, and M. N. Do, Bayesian group-sparse modeling and variational inference, IEEE Transactions on Signal Processing, vol. 62, no. 11, pp. 2906-2921, Nov. 2014.

  21. D. T. Vu, B. Chidester, H. Yang, M. N. Do, and J. Lu, Efficient hybrid tree-based stereo matching with applications to postcapture image refocusing, IEEE Transactions on Image Processing, vol. 23, no. 8, pp. 3428-3442, Aug. 2014.

  22. A. L. N. Targino da Costa and M. N. Do, A retina-based perceptually lossless limit and a Gaussian foveation scheme with loss control, IEEE Journal of Selected Topics in Signal Processing, vol. 8, no. 3, pp. 438-453, 2014.

  23. B. Ham, D. Min, C. Oh, M. N. Do, and K. Sohn, Probability-based rendering for view synthesis, IEEE Transactions on Image Processing, vol. 23, no. 2, pp. 870-884, 2014.

  24. D. Min, J. Lu, and M. N. Do, Joint histogram-based cost aggregation for stereo matching, IEEE Transactions on Pattern Analysis and Machine Intelligence,, vol. 35, no. 10, pp. 2539-2545, 2013.

  25. H. M. Nguyen, X. Peng, M. N. Do, and Z.-P. Liang, Denoising MR spectroscopic imaging data with low-rank approximations, IEEE Trans. on Biomedical Engineering, vol. 60, no. 1, pp. 78-89, 2013.

  26. V.-A. Nguyen, D. Min, and M. N. Do, Efficient techniques for depth video compression using weighted mode filtering, IEEE Transactions on Circuits and Systems for Video Technology, vol. 23, no. 2, pp. 189-202, 2013.

  27. M. N. Do and Y. M. Lu, Multidimensional filter banks and multiscale geometric representations, Foundations and Trends in Signal Processing, vol. 5, issue. 3, pp. 157-264, 2012.

  28. M. Mir, S. D. Babacan, M. Bednarz, M. N. Do, I. Golding, and G. Popescu, Visualizing Escherichia coli sub-cellular structure using sparse deconvolution spatial light interference tomography, PLoS ONE, vol. 7, June 2012.

  29. D. Min, J. Lu, and M. N. Do, Depth video enhancement based on weighted mode filtering, IEEE Transactions on Image Processing, vol. 21, no. 3, pp. 1176-1190, Mar. 2012.

  30. M. N. Do, D. Marchand-Maillet, and M. Vetterli, On the bandwidth of the plenoptic function, IEEE Transactions on Image Processing, vol. 21, no. 2, pp. 708-717, Feb. 2012.

  31. S. D. Babacan, Z. Wang, M. Do, and G. Popescu, Cell imaging beyond the diffraction limit using sparse deconvolution spatial light interference microscopy, Biomedical Optics Express, vol. 2, no. 7, pp. 1815-1827, July 2011.

  32. H. Pham, H. Ding, N. Sobh, M. Do, S. Patel, and G. Popescu, Off-axis quantitative phase imaging processing using CUDA: toward real-time applications, Biomedical Optics Express, vol. 2, no. 7, pp. 1781-1793, July 2011.

  33. A. J. Dapore, M. R. King, J. Harter, S. Sarwate, M. L. Oelze, J. A. Zagzebski, M. N. Do, T. J. Hall, and W. D. O'Brien, Analysis of human fibroadenomas using three-dimensional impedance maps, IEEE Transactions on Medical Imaging, vol. 30, no. 6, pp. 1206-1213, June 2011.

  34. M. N. Do, Q. H. Nguyen, H. T. Nguyen, D. Kubacki, and Sanjay J. Patel, Immersive visual communication with depth cameras and parallel computing, IEEE Signal Processing Magazine, vol. 28, pp. 58-66, Jan. 2011.

  35. K. L. Law and M. N. Do, Multidimensional filter bank signal reconstruction from multichannel acquisition, IEEE Transactions on Image Processing, vol. 20, pp. 317-326, Feb. 2011.

  36. M. Maitre and M. N. Do, Depth and depth-color coding using shape-adaptive wavelets, Journal of Visual Communication and Image Representation, Special Issue on Multicamera Imaging, pp. 513-522, July 2010.

  37. A. L. Cunha, M. N. Do, and M. Vetterli, On the information rates of the plenoptic function, IEEE Transactions on Information Theory, vol. 56, pp. 1306-1321, Mar. 2010.

  38. D. Lin, X. Huang, Q. Nguyen, J. Blackburn, C. Rodrigues, T. Huang, M. N. Do, S. Patel, and W.-M. Hwu, Parallelization of video processing: from programming models to applications, IEEE Signal Processing Magazine, pp. 103-112, Nov. 2009.

  39. K. L. Law, R. M. Fossum, and M. N. Do, Generic invertibility of multidimensional FIR filter banks and MIMO systems, IEEE Transactions on Signal Processing, vol. 57, no. 11, pp. 4282-4291, Nov. 2009.

  40. Y. M. Lu, M. N. Do, and R. S. Laugesen, A computable Fourier condition generating alias-free sampling lattices, IEEE Transactions on Signal Processing, vol. 57, no. 5, pp. 1768-1782, May 2009.

  41. R. L. Morrison, M. N. Do, and D. C. Munson, MCA: a multichannel approach to SAR autofocus, IEEE Transactions on Image Processing, vol. 18, no. 4, pp. 840-853, Apr. 2009.

  42. H. T. Nguyen and M. N. Do, Error analysis for image-based rendering with depth information, IEEE Transactions on Image Processing, vol. 18, no. 4, pp. 703-716, Apr. 2009.

  43. H. M. Nguyen, B. P. Sutton, R. L. Morrison, and M. N. Do, Joint estimation and correction of geometric distortions for EPI functional MRI using harmonic retrieval, IEEE Transactions on Medical Imaging, vol. 28, no. 3, pp. 423-434, Mar. 2009.

  44. H. T. Nguyen and M. N. Do, Hybrid filter banks with fractional delays: Minimax design and application to multichannel sampling, IEEE Transactions on Signal Processing, vol. 56, no. 7, pp. 3180-3190, July 2008.

  45. M. Maitre, Y. Shinagawa, and M. N. Do, Wavelet-based joint estimation and encoding of depth-image-based representations for free-viewpoint rendering, IEEE Transactions on Image Processing, vol. 17, no. 6, pp. 946-957, June 2008.

  46. Y. M. Lu and M. N. Do, A theory for sampling signals from a union of subspaces, IEEE Transactions on Signal Processing, vol. 56, no. 6, pp. 2334-2345, June 2008.

  47. Y. M. Lu and M. N. Do, A mapping-based design for nonsubsampled hourglass filter banks in arbitrary dimensions, IEEE Transactions on Signal Processing, vol. 56, no. 4, pp. 1466-1478, Apr. 2008.

  48. Y. M. Lu and M. N. Do, Sampling signals from a union of subspaces, IEEE Signal Processing Magazine, Special Issue on Compressive Sampling, vol. 25, no. 2, pp. 41-47, Mar. 2008.

  49. R. L. Morrison, M. N. Do, and D. C. Munson, SAR image autofocus by sharpness optimization: a theoretical study, IEEE Transactions on Image Processing, vol. 16, no. 9, pp. 2309-2321, Sep. 2007.

  50. A. L. Cunha and M. N. Do, On two-channel filter banks with directional vanishing moments, IEEE Transactions on Image Processing, vol. 16, no. 5, pp. 1207-1219, May 2007.

  51. Y. M. Lu and M. N. Do, Multidimensional directional filter banks and surfacelets, IEEE Transactions on Image Processing, vol. 16, no. 4, pp. 918-931, Apr. 2007.
    Surfacelet movie (Animated GIF file showing surfacelet atoms in 3D as videos).

  52. D. Xu and M. N. Do, On the number of rectangular tilings, IEEE Transactions on Image Processing, vol. 15, no. 10, pp. 3225-3230, Oct. 2006.

  53. J. Zhou and M. N. Do, Multidimensional multichannel FIR deconvolution using Grobner bases, IEEE Transactions on Image Processing, vol. 15, no. 10, pp. 2998-3007, Oct. 2006.

  54. A. L. Cunha, J. Zhou, and M. N. Do, The nonsubsampled contourlet transform: Theory, design, and applications, IEEE Transactions on Image Processing, vol. 15, no. 10, pp. 3089-3101, Oct. 2006.

  55. Y. Huang, I. Pollak, M. N. Do, and C. A. Bouman, Fast search for best representations in multitree dictionaries, IEEE Transactions on Image Processing, vol. 15, no. 7, pp. 1779-1793, July 2006.

  56. D. D.-Y. Po and M. N. Do, Directional multiscale modeling of images using the contourlet transform, IEEE Transactions on Image Processing, vol. 15, no. 6, pp. 1610-1620, June 2006.

  57. Y. Huang, I. Pollak, C.A. Bouman, and M. N. Do, Best basis search in lapped dictionaries, IEEE Transactions on Signal Processing, vol. 54, no. 2, pp. 651-664, Feb. 2006.

  58. J. Zhou, M. N. Do, and J. Kovacevic, Special paraunitary matrices, Cayley transform, and multidimensional orthogonal filter banks, IEEE Transactions on Image Processing, vol. 15, no. 2, pp. 511-519, Feb. 2006.

  59. M. N. Do and M. Vetterli, The contourlet transform: an efficient directional multiresolution image representation, IEEE Transactions Image on Processing, vol. 14, no. 12, pp. 2091-2106, Dec. 2005. Contourlet toolbox (Matlab source code that implements the contourlet transform and its utility functions).
    Contourlet movie [QuickTime video compares non-linear approximations using wavelets (DWT2) and contourlets (PDFB)].

  60. J. Zhou, M. N. Do, and J. Kovacevic, Multidimensional orthogonal filter bank characterization and design using the Cayley transform, IEEE Transactions on Image Processing, vol. 14, no. 6, pp. 760-769, June 2005.

  61. R. Shukla, P. L. Dragotti, M. N. Do and M. Vetterli, Rate-distortion optimized tree structured compression algorithms for piecewise smooth images, IEEE Transactions on Image Processing, vol. 14, pp. 343-359, Mar. 2005.

  62. C. Xu, D. L. Marks, M. N. Do, and S. A. Boppart, Separation of absorption and scattering profiles in spectroscopic optical coherence tomography using a least-squares algorithm, Optics Express, vol. 12, no. 20, pp. 4790-4803, Oct. 2004.

  63. M. N. Do and M. Vetterli, Framing pyramids, IEEE Transactions on Signal Processing, vol. 51, pp. 2329-2342, Sep. 2003.  PDF | Postscript
    Laplacian pyramid toolbox [Matlab source code that implements the Laplacian pyramid (in any dimension) with the new reconstruction method in the paper].

  64. M. N. Do, Fast approximation of Kullback-Leibler distance for dependence trees and hidden Markov models, IEEE Signal Processing Letters, vol. 10, pp. 115-118, Apr. 2003.  PDF | Postscript

  65. M. N. Do and M. Vetterli, The finite ridgelet transform for image representation, IEEE Transactions on Image Processing, vol. 12, pp. 16-28, Jan. 2003.  PDF | Postscript
    FRIT Toolbox (Matlab source code that implements the transforms in the paper).
    FRIT movie (QuickTime video compares non-linear approximations using wavelets and ridgelets).

  66. M. N. Do and M. Vetterli, Rotation invariant texture characterization and retrieval using steerable wavelet-domain hidden Markov models, IEEE Transactions on Multimedia, vol. 4, pp. 517-527, Dec. 2002.  PDF | Postscript

  67. M. N. Do and M. Vetterli, Wavelet-based texture retrieval using generalized Gaussian density and Kullback-Leibler distance, IEEE Transactions on Image Processing, vol. 11, pp. 146-158, Feb. 2002.  PDF | Postscript
    WaveTex (Matlab source code that implements the algorithms and experiments in the paper).


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