Xiaolin Wu

Professor

NSERC Senior Industrial Research Chair

IEEE Fellow

McMaster Distinguished Engineering Professor

Associated Editor, IEEE Transactions on Image Processing

 

Department of Electrical & Computer Engineering
ITB A315
McMaster University
Hamilton, Ontario, Canada, L8G 4K1

email: xwu at ece.mcmaster.ca


COURSES: Digital Logic (2DI4); Discrete Methods (703); Data Structures and Algorithms (2SI4) ; Image Processing (4TN4); Numerical Analysis (3SK3); Parallel and Distributed Computing (709)


RESEARCH:

My general research interests are visual/multimedia computing and communications. I have published numerous algorithms for computer graphics and image processing (image coding in particular), some of which are being used by practitioners, such as a fast optimal color quantizer, and a Context-based Adaptive Lossless Image Codec CALIC(executable) .

 

My cool idea for information display

(featured in MIT Technology Review http://m.technologyreview.com/blog/arxiv/27490/)

Temporal Psychovisual Modulation (TPVM)

Via an ingenious interplay of critical flicker frequency of human vision, high refresh-rate digital display and optoelectronic viewing devices, TPVM is a new display paradigm that differs fundamentally, in design principle, user experience and cost effectiveness, from head-mounted display (HMD) technology and from Sony screen sharing technology, while offering more and exciting functionalities.

 

visor7a

The scientific principle of TPVM: atom frames emitted by high-speed display are weighted by active LC glasses and perceived by the human visual system (HSV) as an image. TPVM allows concurrent multiple self-intended exhibitions via a common display medium, an optoelectronic-psychovisual process modeled by non-negative matrix factorization. Different images are perceived by different viewers whose LC glasses modulate the same sequence of atom frames differently (see below).

 

visor7bSee how TPVM works

In virtual reality (VR) and augmented reality (AR), TPVM allows

 Examples in 3D medical visualization;   Examples in security/privacy protection.

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Our book: Network-aware Source Coding and Communication, Cambridge University Press, 2011 new book

Selected Publications: 

Machine learning

 

·       X. Zhang, X. Wu, ``On numerosity of deep neural networks``, in Advances in Neural Information Processing Systems (NIPS), Dec., 2020.

 

·       X Wu, Q Gao, Z Li, S Li, ``A fast and practical CNN method for artful image regeneration``, ACM SIGGRAPH 2020.

 

·       X. Zhang, X. Wu, X. Zhai, X. Ben, C. Tu, ``DAVD-Net: Deep audio-aided video decompression of talking heads``, in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 12335-12344, June, 2020.

 

·       Q. Gao, X. Shu and X. Wu, ``Deep restoration of vintage photographs from scanned halftone prints``, in Proc. of 2019 International Conference on Computer Vision (ICCV), pp. 4120-4129, 2019.

 

·       X. Wu, X. Zhang, X. Shu, ``Cognitive deficit of deep learning in numerosity``, in Proc. of the Thirty-Third AAAI Conference on Artificial Intelligence, pp. 1303-1310, 2019.

 

·       Z. Chi, X. Shu and X. Wu, ``Joint demosaicking and blind deblurring using deep convolutional neural network``, in 2019 IEEE International Conference on Image Processing, pp. 2169-2173, 2019.

 

·       X. Zhang and X. Wu, "Near-lossless loo-constrained image decompression via deep neural network.", in Proc. of 2019 Data Compression Conference, pp. 33-42, 2019.

 

 

Image Processing

 

·       X. Wu, D. Gao, Q. Chen, “Multispectral imaging via nanostructured random broadband filtering", Optics Express, vol. 28, no. 4, pp. 4859-4875, Apr. 2020.

·       X. Shu, X. Wu, “Locally adaptive rank-constrained optimal tone mapping", ACM Transactions on Graphics, vol. 37, no. 3, pp. 3801-3810, Aug. 2018.

·       D. Gao, X. Wu, “Multispectral image restoration via inter- and intra-block sparse estimation based on physically-induced joint spatiospectral structures", IEEE Transactions on Image Processing, vol. 27, no. 8, pp. 4038-4051, Aug. 2018.

·       X. Shu, X. Wu, “Real-time high-fidelity compression for extremely high frame rate video cameras", IEEE Transactions on Computational Imaging, vol. 4, no. 1, pp. 172-180, March 2018.

·       Z. Li, X. Wu, “Learning-based restoration of backlit images", IEEE Transactions on Image Processing, vol. 27, no. 2, pp. 976-986, Feb. 2018.

·       Y. Liu, X. Wu, G. Shi, “Image enhancement by entropy maximization and quantization resolution upconversion”, IEEE Transactions on Image Processing, vol. 25, no. 10, pp. 4815-4828, Oct. 2016.

·       X. Liu, X. Wu, J. Zhou, D. Zhao, “Data-driven sparsity-based restoration of JPEG compressed images in dual transform-pixel domain", IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), pp. 5171-5178, 2015.

·       X. Wu, Z. Li, X. Deng, ``Video restoration against yin-yang phasing", 2015 IEEE Int. Conf. on Computer Vision (ICCV), pp. 549-557, 2015.

·       H. Xu, G. Zhai, X. Wu, X. Yang, "Generalized equalization model for contrast enhancement", IEEE Trans. on Multimedia, vol. 16, no. 1, pp. 68-82, January 2014.

·       W. Dong, G. Shi, X. Wu, L. Zhang, "A learning-based method for compressive image recovery", J. of Visual Comm. and Image Repr., vol. 24, no. 7, pp. 1055-1063, Oct. 2013.

·       D. Gao, D. Liu, X. Xie, X. Wu, G. Shi, "High-resolution multispectral imaging with random coded exposure", Journal of Applied Remote Sensing, vol. 7, no. 1, Sept. 2013.

·       Y. Niu, X. Wu, X. Zhang, G. Shi, “Model-based adaptive resolution upconversion of degraded images", J. Visual Communication and Image Representation 23(7), pp. 1144-1157, July 2012.

·       X. Wu, W. Dong, X. Zhang and G. Shi, “Model-assisted adaptive recovery of compressive sensing with imaging applications", IEEE Trans. on Image Processing, vol. 21, no. 2, pp. 451-458, Feb. 2012.

·       D. Gao, X. Wu, G. Shi, L. Zhang, "Color demosaicking with an image formation model and adaptive PCA", J. Visual Communication and Image Representation 23(7), pp. 1019-1030, 2012.

·       W. Dong, L. Zhang, G. Shi, X. Wu, “Image deblurring and super-resolution by adaptive sparse domain selection and adaptive regularization", IEEE Trans. on Image Processing,

vol. 20, no. 7, pp. 1838-1857, July 2011.

 

Image Coding

·       X. Liu, G. Cheung, X. Wu, D. Zhao, “Random walk graph Laplacian-based smoothness prior for soft decoding of JPEG images”, IEEE Transactions on Image Processing, vol. 25, no. 11, pp. 509-524, Nov. 2016.

·       X. Liu, X. Wu, J. Zhou, D. Zhao, "Data-driven soft decoding of compressed images in dual transform-pixel domain", IEEE Transactions on Image Processing, vol. 25, no. 4, pp. 1649-1659, Apr. 2016.

·       S. Chuah, S. Dumitrescu, X. Wu, "L2 optimized predictive image coding with Loo bound", IEEE Trans. on Image Processing, vol. 22, no. 12, pp. 5271-5281, Dec. 2013.

·       J. Zhou, X. Wu, L. Zhang, “L2 restoration of L1-decoded images via soft-decision estimation", IEEE Trans. on Image Processing, vol. 21, no. 12, pp. 4797-4807, Dec. 2012.

·       Y. Niu, X. Wu, G. Shi, X. Wang, “Edge-based perceptual image coding", IEEE Trans. on Image Processing, vol. 21, no. 4, pp. 1899-1910, April 2012.

 

Signal processing for information displays

·       L. Jiao, X. Shu, Y. Cheng, X. Wu, "Optimal backlight modulation with crosstalk control in stereoscopic display", IEEE Journal of Display Technology, vol. 11, no. 2, pp. 157-164, Feb. 2015.

·       G. Zhai, X. Wu, "Defeating camcorder piracy by temporal psychovisual modulation", Journal of Display Technology, vol. 10, no. 9, pp. 754-757, Sept. 2014.

·       G. Zhai, X. Wu, "Multiuser collaborative viewport via temporal psychovisual modulation", IEEE Signal Processing Magazine, vol. 31, no. 5, pp. 144-149, May 2014.

·       L. Jiao, X. Shu, Y. Cheng, X. Wu, "Optimal backlight modulation with crosstalk control in stereoscopic display",  Journal of Display Technology, vol. 10, no. 10, Oct. 2014.

·       X. Wu, G. Zhai, “Temporal psychovisual modulation: a new paradigm of information display", IEEE Signal Processing Magazine, vol. 30, no. 1, pp. 136-141, Jan. 2013.

·       X. Shu, X. Wu, S. Forchhammer, “Optimal local dimming for LC image formation with controllable backlighting", IEEE Trans. on Image Processing, vol. 22, no. 1, pp. 166-173, Jan. 2013.

 

Network-aware source coding and communication

 

·       J. Wang, X. Wu, J. Sun, S. Yu, "On two-stage sequential coding of correlated sources", IEEE Trans. on Information Theory, vol. 60, no. 12, pp. 7490-7505, Dec. 2014.

·       X. Wu, H. D. Mittelmann, X. Wang, J. Wang, “On computation of performance bounds of optimal index assignment", IEEE Trans. on Communications, vol. 59, no. 12, pp. 3229-3233, Dec. 2011.

·       M. Shao, S. Dumitrescu and X. Wu, “Layered multicast with inter-layer network coding for multimedia streaming", IEEE Trans. on Multimedia, vol. 13, no. 2, pp. 353-365, March 2011.

·       J. Wang, J. Chen, and X. Wu, “On the sum rate of Gaussian multiterminal source coding: new proofs and results", IEEE Trans. on Information Theory, vol. 56, no. 8, pp. 3946-3960, Aug. 2010.

·       X. Wang and X. Wu, “Index assignment optimization for joint source-channel MAP decoding", IEEE Trans. on Communications, vol. 58, no. 3, pp. 901-910, Mar. 2010.

·       Z. Sun, M. Shao, J. Chen, K. Wong, X. Wu, “Achieving the rate-distortion bound with low-density generator matrix codes," IEEE Trans. on Communications, vol. 58, no. 6, pp. 1643-1653, June, 2010.

·       X. Wang and X. Wu, "Index assignment optimization for joint source-channel MAP decoding", IEEE Trans. on Communications, vol. 58, no. 3, pp. 901-910, Mar 2010.

·       S. Dumitrescu and X. Wu, “On properties of locally optimal multiple description scalar quantizers with convex cells", IEEE Trans. on Information Theory, vol. 55, no. 12, pp. 5591-5606, Dec. 2009.

 

 

 

Signal quantization and source coding

 

·       L.Wang, X.Wu, G. Shi, “Binned progressive quantization for compressive sensing", IEEE Trans. on Image Processing, vol. 21, no. 6, pp. 2980-2990, June 2012.

 

Biomedical Imaging

 

 

Steganalysis and Watermarking