Professor Hong Ren Wu

Royal Melbourne Institute of Technology, Australia Website: http://www.rmit.edu.au/staff/hong-ren-wu Email:

Biography

Hong Ren Wu received BEng. and MEng. from University of Science and Technology, Beijing (formerly Beijing University of Iron and Steel Technology), P.R. China, in 1982 and 1985, respectively. He received the PhD in Electrical and Computer Engineering from the University of Wollongong, N.S.W. Australia, in 1990.

 

Dr Wu was on academic staff of Chisholm Institute of Technology and then Monash University, Melbourne, Australia from April 1990 to January 2005, last as an Associate Professor in Digital Systems. Since February 2005, Dr Wu has been with Royal Melbourne Institute of Technology, Australia, as Professor of Visual Communications Engineering, serving concurrently from 2005 to 2010 as Discipline Head of Computer and Network Engineering in School of Electrical and Computer Engineering.

 

Professor Wu’s research interests include fast DSP (digital signal processing) algorithms, digital picture compression and quality assessment, video processing and enhancement, embedded DSP systems and their industrial applications. He has published extensively in refereed journals as well as conferences. His significant contributions in the areas relevant to digital picture compression and quality assessment include identification and definition of digital video stationary area temporal fluctuation coding artefacts in 1995-1997, the no-reference HVS (human visual system) based picture blocking metric in 1996-1997, the multi-channel vision model based video blocking impairment metric in 2000-2002, the multi-channel vision model based video ringing impairment metric in 2003, perceptual monochrome image coding based on vision model and RpD optimisation in 2001-2004, perceptually lossless coding of medical images in 2003-2006, perceptual colour image coding based on vision model and RpD optimisation in 2003-2010, post-filtering for reduction of digital video temporal fluctuation artefacts in 2008-2010, and introduction of RpD optimisation framework for inter-frame and inter-view coding of 3-D video in 2011.

 

Professor Wu is a co-editor of the book, Digital Video Image Quality and Perceptual Coding, CRC Press, 2006 (ISBN: 0-8247-2777-0). He is a guest editor for the special issue on “Multimedia Communication Services” of Circuits, Systems and Signal Processing, No. 3, 2001, the special issue on “Quality Issues on Mobile Multimedia Broadcasting” of the IEEE Transactions on Broadcasting, Vol. 54, No.3, Pt II, September 2008, and the special issue on “QoE Management in Emerging Multimedia Services” of IEEE Communications Magazine, April 2012.

 

Title

Perceptual Coding of Digital Pictures - A leap of insight

Abstract

When William M. Goodall of Bell Laboratories reported at IRE [a] National Convention in 1949 his implementation of the world-first digital video system using PCM (pulse code modulation) [1], few would realize that the end of the analogue television (TV), a relatively new invention in those days which grabbed the fascination of the general population around the globe, had just been announced. Replacing the analogue television will be a flurry of digital visual communication and entertainment applications unimaginable or considered impossible at the time. It immediately prompted a major invention in digital signal coding for modern communications widely known as DPCM (differential pulse code modulation) [2] as well as opened up an inciting field known as digital picture coding (DPC) [b]. Waite we had to, however, for four more decades before the first generation international standards (i.e., ITU-T H.120 [4], ITU-T H.261 [5] and JPEG [6]) started to emerge for digital picture compression, followed by a proliferation of digital picture compression products and applications as we are witnessing today, including video telephony, video conferencing, digital photography (cameras), digital TV broadcasting, IPTV [c] , IP CCTV [d], video streaming and on-demand services, DVD and high definition (HD) and 3-D DVD/Blu-ray Disc (BD) products, medical Picture Archive and Communication System (PACS), remote sensing, broadband wireless and multimedia communications.

 

Developments of digital picture coding have been underpinned to date by three fundamental theories, i.e., Shannon-Nyquist sampling theory for digital representation of visual signals or picture waveforms [7], Shannon’s entropy theory which defines the lower-bound for information lossless picture compression [8], and Shannon’s rate-distortion (R-D) theory for lossy picture compression [9], notwithstanding these theories are applicable to a much wider range of signals than pictures. This lecture reviews generations of relentless research efforts of advancing DPC theories on human perception basis [10-12], i.e., expanding Shannon-Nyquist sampling theory by compressive sampling for reconstruction of signals without perceptual loss [13]; pairing Shannon’s information entropy with perceptual entropy [14] setting the lower-bound for perceptually lossless coding of visual signals [15-16]; enhancing Shannon’s R-D theory by introducing Rate-perceptual-Distortion (RpD) optimisation for perceptually lossy picture compression [14,17]. It elaborates the importance and the relevance of research and development in perceptual picture coding (PPC) as three-fold in terms of theoretical development, undisputed practical compression performance gains, and paradigm shift from technology dictated bitrate constrained to user-centric visual communication and entertainment services.

 

The history of research and development in human visual system (HVS) based perceptual picture coding is longer than what many care to admit [18,12]. This lecture examines successful approaches to perceptual picture coding design in three broad categories which were based on low-level HVS models, i.e., JND (Just Noticeable Difference) model based predictive (including motion-compensated video) coding, perceptual quantisation strategies based on both JND and supra-threshold HVS models, and RpD optimisation, highlighting advantages of these approaches and challenges which each faces. A number of gaps are identified in relation to perceptually lossless and perceptually lossy coding, perceptual coding of monochrome and colour images, and intra-frame and inter-frame or inter-view video coding. It will shine spotlight on importance, relevance and urgency of PPC research which have become increasingly obvious to research and professional communities and industries in order to develop future generations of high quality picture coding standards, products, systems and applications such as super- or ultra-high definition (SHD or UHD) imaging and video systems [19], digital cinema distribution systems, full HD 3-D video/TV, immersive interactive visual systems, and PACS for telemedicine/telehealth applications. The time has come that the visual communication services and entertainment be transformed from the “best efforts” to quality assured practice for the associated industries to be sustainable in the long run. It concludes by highlighting a number of theoretical and practical challenges in this fascinating field of engineering and technology which has been transforming our way of life.

 

 

[a] IRE stands for the Institute of Radio Engineers, a predecessor of the IEEE (Institute of Electrical and Electronic Engineers).

[b] Digital picture coding termed here follows the traditional definition and refers to digital coding of still images, video, image sequences or motion pictures [3].

[c] IPTV stands for Internet Protocol TV.

[d] CCTV stands for Closed Circuits TV.

 

References

[1]	W.M. Goodall, “Television by pulse code modulation,” Bell Systems Technical Journal, 28:33-49, January 1951.
[2]	Office of the Home Secretary, National Academy of Sciences. C.C. Cutler, Biographical Memoirs, 85:62-82, 2004 (ISBN-10: 0-309-10363-0).
[3]	A. N. Netravali and B. G. Haskell, Digital Pictures: Representation, Compression and Standards. New York, NY: Plenum Press, 1995.
[4]	ITU-T, “Codecs for Videoconferencing Using Primary Digital Group Transmission,” Rec. H.120, International Telecommunication Union, Telecommunication Standardization Sector, March 1993.
[5]	ITU-T, “Video Codec for Audiovisual Services at p x 64 kbits,” Rec. H.261 (ver. 1, 1988), International Telecommunication Union, Telecommunication Standardization Sector, December 1990.
[6]	ITU-T, “ISO/IEC 10918-1: Information Technology - Digital Compression and Coding of Continuous-tone Still Images – Requirements and Guidelines,” Rec. T.81, International Telecommunication Union, Telecommunication Standardization Sector, September 1992.
[7]	C.E. Shannon, “Communication in the Presence of Noise,” Proceedings of The IRE, vol. 37, pp. 10–21, January 1949.
[8]	C.E. Shannon, “A Mathematical Theory of Communication,” Bell System Technical Journal, 27:379-623, 1948.
[9]	C.E. Shannon, “Coding Theorems for a Discrete Source With a Fidelity Criterion,” Institute of Radio Engineers, International Convention Record, vol. 7, no. 4, pp. 142–163, 1959.
[10]	A.J. Seyler and Z.L. Budrikis, “Measurements of temporal adaptation to spatial detain vision,” Nature, 184:1215-1217, Oct. 1959.
[11]	J. O. Limb, “Source-Receiver Encoding of Television Signals,” Proceedings of The IEEE, vol. 55, pp. 364–379, March 1967.
[12]	H.R. Wu, A.R. Reibman, W. Lin, F. Pereira and S.S. Hemami, “Perceptual Visual Signal Compression and Transmission,” (invited paper to appear) Special Issue on Perception Based Media Processing, Proc. IEEE, September 2013.
[13]	R. G. Baraniuk, E. Candes, R. Nowak, and M. Vetterli, “Compressive sampling,” IEEE Signal Processing Magazine, pp. 12–13, March 2008.
[14]	N. Jayant, J. Johnston, and R. Safranek, “Signal compression based on models of human perception,” Proc. IEEE, 81:1385-1422, October 1993.
[15]	A. B. Watson, “Receptive fields and visual representations,” in Proc. SPIE-Human Vision, Visual Processing, and Digital Display, pp. 190–197, 1989.
[16]	D. Wu, D. M. Tan, M. Baird, J. DeCampo, C. White, and H. R. Wu, “Perceptually lossless medical image coding,” IEEE Transactions on Medical Imaging, vol. 25, pp. 335–344, March 2006.
[17]	H.R. Wu and K.R. Rao, Eds. Digital Video Image Quality and Perceptual Coding. CRC Press, 2006.
[18]	J. O. Limb and C. B. Rubinstein, “On the Design of Quantizers for DPCM Coders: A Functional Relationship Between Visibility, Probability and Masking,” IEEE Transactions on Communications, vol. COM-26, pp. 573–578, May 1978.
[19]	ITU-R, “Parameter values for ultra-high definition systems for production and international programme exchange,” Rec. BT.2020, Aug. 2012.