Publications

Pre-prints

  1. Joon Hee Choi, Omar A. Elgendy and Stanley H. Chan, ‘‘Image reconstruction for Quanta Image Sensors using deep neural networks’’, submitted to IEEE ICASSP 2018.

  2. Yiheng Chi and Stanley H. Chan, ‘‘Fast and robust recursive filter for image denoising’’, submitted to IEEE ICASSP 2018.

  3. Omar A. Elgendy and Stanley H. Chan, ‘‘Optimal Threshold Design for Quanta Image Sensor’’, submitted to IEEE Trans. Computational Imaging, Oct 2017.

Journals

  1. Stanley H. Chan, Todd Zickler, and Yue M. Lu, ‘‘Understanding symmetric smoothing filters: A Gaussian mixture model perspective’’, IEEE Trans. Image Process., vol. 26, no. 11, pp. 5107–5121, Nov. 2017.

  2. Stanley H. Chan, Xiran Wang, and Omar Elgendy, ‘‘Plug-and-Play ADMM for image restoration: Fixed point convergence and applications’’, IEEE Trans. Comp. Imaging, vol. 3, no. 5, pp.84–98, Mar. 2017. [CODE]

  3. Stanley H. Chan, Omar Elgendy and Xiran Wang, ‘‘Images from bits: Non-iterative image reconstruction for quanta image sensors’’, MDPI Sensors Special Issue on Photon-Counting Image Sensors, vol. 16, no. 11, paper 1961, pp.1-21, Nov. 2016.

  4. Enming Luo, Stanley H. Chan, and Truong Q. Nguyen, ‘‘Adaptive image denoising by mixture adaptation’’, IEEE Trans. Image Process., vol. 25, no. 10., pp.4489–4503, Oct. 2016. [CODE]

  5. Chien-Sheng Liao, Joon Hee Choi, Delong Zhang, Stanley H. Chan, and Ji-xin Cheng, ‘‘Denoising stimulated Raman spectroscopic images by total variation minimization’’, Journal of Physical Chemistry C, vol. 119, no. 33, pp.19397–19403, Jul. 2015. [CODE]

  6. Enming Luo, Stanley H. Chan, and Truong Q. Nguyen, ‘‘Adaptive image denoising by targeted databases’’, IEEE Trans. Image Process., vol. 24, no. 7, pp.2167-2181, Jul. 2015. [CODE]

  7. Lee-Kang Liu, Stanley H. Chan, and Truong Q. Nguyen, ‘‘Depth Reconstruction from Sparse Samples: Representation, algorithm, and sampling’’, IEEE Trans. Image Process., vol. 24, no. 6, pp. 1983-1996, Jun. 2015. [CODE]

  8. Stanley H. Chan, Todd Zickler, and Yue M. Lu, ‘‘Monte Carlo non-local means: Random sampling for large-scale image filtering’’, IEEE Trans. Image Process., vol. 23, no. 8, pp. 3711-3725, Aug. 2014. [CODE]

  9. Stanley H. Chan and Edoardo M. Airoldi, ‘‘A consistent histogram estimator for exchangeable graph models’’, Journal of Machine Learning Research Workshop and Conference Proceedings, vol. 32, no. 1, pp. 208-216, 2014. [CODE]

  10. EdoardoM. Airoldi, Thiago B. Costa and Stanley H. Chan, ‘‘Stochastic blockmodel approx- imation of a graphon: Theory and consistent estimation,’’ Advances in Neural Information Processing Systems (NIPS), pp.692–700, Dec. 2013. [CODE]

  11. Stanley H. Chan, Ramsin Khoshabeh, Kristofor B. Gibson, Philip E. Gill and Truong Q. Nguyen, ‘‘An augmented Lagrangian method for total variation video restoration,’’ IEEE Trans. Image Process., vol. 20, issue 11, pp.3097–3111, Nov. 2011. [CODE]

  12. Stanley H. Chan and Truong Q. Nguyen, ‘‘LCD motion blur: modeling, analysis and algorithm,’’ IEEE Trans. Image Process., vol.20, issue 8, pp.2352–2365, Aug. 2011.

  13. Stanley H. Chan, Thomas X. Wu and Truong Q. Nguyen, ‘‘Comparison of two frame rate conversion schemes for reducing LCD motion blurs,’’ IEEE Signal Process. Letters, vol. 17, issue 9, pp.783–786, Sep. 2010.

  14. Stanley H. Chan, Alfred K. Wong, and Edmund Y. Lam, ‘‘Initialization for robust inverse synthesis of phase-shifting masks in optical projection lithography,’’ Optics Express, vol. 16, no. 9, pp.14746–14760, Sep. 2008.

Conference

  1. Xiran Wang and Stanley H. Chan, ‘‘Parameter-free Plug-and-Play ADMM for image restoration’’, IEEE ICASSP, pp.1323-1327, New Orleans, Louisiana, Mar. 2017.

  2. Chiman Kwan, Joon Hee Choi, Stanley H. Chan, Jin Zhou, and Bence Budavari, ‘‘Resolution enhancement for hyperspectral images: A super-resolution and fusion approach’’, IEEE ICASSP, pp.6180-6184, New Orleans, Louisiana, Mar. 2017.

  3. (Best Paper Award) Omar Elgendy and Stanley H. Chan, ‘‘Image reconstruction and threshold design for quanta image sensors’’, IEEE ICIP, pp.978-982, Phoenix, Arizona, Sep. 2016.

  4. Stanley H. Chan, Enming Luo, and Truong Q. Nguyen, ‘‘Adaptive patch-based image denoising by EM adaptation’’, IEEE GlobalSIP, pp. 810-814, Orlando, Florida, Dec. 2015.

  5. Stanley H. Chan, Todd Zickler, Yue M. Lu, ‘‘Understanding symmetric smoothing filters via Gaussian mixtures’’, IEEE ICIP, pp. 2500-2504, Quebec City, Canada, Sep. 2015.

  6. Stanley H. Chan, and Yue M. Lu, ‘‘Efficient image reconstruction for giga-pixel quantum image sensors’’, IEEE GlobalSIP, pp. 312-316, Atlanta, Georgia, Dec. 2014.

  7. Enming Luo, Stanle H. Chan, and Truong Q. Nguyen, ‘‘Image Denoising by Targeted External Databases’’, IEEE ICASSP, pp. 3019-3023, Florence, Italy, May 2014.

  8. Stanley H. Chan, Thiago B. Costa and Edoardo M. Airoldi, ‘‘Estimation of exchangeable random graph models by stochastic blockmodel approximation,’’ IEEE GlobalSIP, pp.293-296, Austin, Texas, Dec. 2013.

  9. Enming Luo, Stanley H. Chan, Shenjun Pan and Truong Q. Nguyen, ‘‘Adaptive non- local means for multiview image denoising - searching for the right patches via a statistical approach,’’ IEEE ICIP, Melbourne, Australia, Sep. 2013.

  10. Stanley H. Chan, Todd Zickler and Yue M. Lu, ‘‘Fast non-local filtering by random sampling: it works, especially for large images,’’ IEEE ICASSP, pp.1603-1607, Vancouver, Canada, May 2013.

  11. Daniel Pipa, Stanley H. Chan and Truong Q. Nguyen, ‘‘Directional decomposition based total variation image restoration,’’ EUSIPCO, pp. 1558-1562, Bucharest, Romania, Aug. 2012.

  12. Lee-Kang Liu, Stanley H. Chan and Truong Q. Nguyen, ‘‘Do we really need Gaussian filters for feature point detection?’’ EUSIPCO, pp. 131-135, Bucharest, Romania, Aug. 2012.

  13. Stanley H. Chan and Truong Q. Nguyen, ‘‘Single-image, two-layered, out-of-focus blur removal,’’ Proc. SPIE 8500, pp.1 - 15, San Diego, California, Aug. 2012.

  14. Stanley H. Chan and Truong Q. Nguyen, ‘‘Single image spatial-variant out-of-focus blur removal,’’ IEEE ICIP, pp.677- 680, Brussels, Belgium, Sep. 2011.

  15. Stanley H. Chan, Ankit K. Jain, Truong Q. Nguyen and Edmund Y. Lam, ‘‘Bounds for the condition numbers of spatially variant convolution matrices in image restoration problems,’’ OSA Topical Meeting in Signal Recovery and Synthesis (OSA-SRS), Paper SMA4, Jul. 2011.

  16. Ramsin Khoshabeh, Stanley H. Chan and Truong Q. Nguyen, ‘‘Spatiotemporal consistency in video disparity estimation,’’ IEEE ICASSP, pp.885-888, Prague, Czech Republic, May 2011.

  17. Stanley H. Chan, Ramsin Khoshabeh, Kristofor B. Gibson, Philip E. Gill and Truong Q. Nguyen, ‘‘An augmented Lagrangian method for video restoration,’’ IEEE ICASSP, pp. 941-944, Prague, Czech Republic, May 2011.

  18. Stanley H. Chan, ‘‘Constructing a sparse convolution matrix for shift varying image restoration problems,’’ IEEE ICIP, pp.3601-3604, Hong Kong, Sep. 2010.

  19. Stanley H. Chan and Truong Q. Nguyen, ‘‘LCD motion blur modeling and simulation,’’ IEEE ICME, pp.400-405, Singapore, Jul. 2010.

  20. Stanley H. Chan, Dung Vo and Truong Q. Nguyen, ‘‘Sub-pixel motion estimation without interpolation,’’ IEEE ICASSP, pp.722-725, Dallas, Texas, Mar. 2010.

  21. Shay Har-Noy, Stanley H. Chan and Truong Q. Nguyen, ‘‘Demosaicing images with mo- tion blur,’’ IEEE ICASSP, pp.1006-1009, Dallas, Texas, Mar. 2010.

  22. Stanley H. Chan and Truong Q. Nguyen, ‘‘Fast LCD motion deblurring by decimation and optimization,’’ IEEE ICASSP, pp.1201-1204, Taipei, Taiwan, Apr. 2009.

  23. Stanley H. Chan and Edmund Y. Lam, ‘‘Inverse image problem of designing phase shifting masks in optical lithography,’’ IEEE ICIP, pp.1832-1835, San Diego, California, Oct. 2008.

  24. Stanley H. Chan, Alfred K.Wong, and Edmund Y. Lam, ‘‘Inverse synthesis of phase shifting mask for optical lithography,’’ in OSA Topical Meeting in Signal Recovery and Synthesis (OSA-SRS), SMD3, Jun. 2007.