Xiaolin Wu

Professor

NSERC Senior Industrial Research Chair

Associated Editor, IEEE Trans. on Image Processing   

IEEE Fellow    

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

phone:  905 525-9140 ext 24190

                             fax:  905 521-2922

email: xwu at ece.mcmaster.ca


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


RESEARCH:

My general research activities are in 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) which was developed jointly with Nasir Memon as a candidate algorithm for the new JPEG lossless standard. CALIC(executable) is widely used as a benchmark in performance evaluation of lossless image codecs.

 

My recent breakthrough in information display technology (patents pending)

(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 MIT’s head-mounted display (HMD) technology and from Sony’s recent 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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I and my students have also developed

·         A highly competitive color demosaicking technique: Primary-Consistent Soft-Decision (PCSD executable: pcsd.rar) color demosaicking algorithm.

·         A highly competitive image interpolation technique: Soft-decision Adaptive Interpolation (SAI executable: sai.rar) algorithm.

·         MARX algorithm (Model-based Adaptive Recovery of Compressive Sensing): (executable: marx.rar).

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

Selected Publications: 

Image Processing

 

·         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.

 

Signal processing for information displays

 

·         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.

 

Image Coding

 

·         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 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