Contains an introduction and reports on seven research projects.Advanced Telecommunications Research ProgramAT&T FellowshipGEM FellowshipU.S. Federal Bureau of InvestigationLucent Technologies FellowshipCharles S. Draper LaboratoryU.S. Navy - Office of Naval Research NDSEG Graduate Fellowshi

Apostolopoulos, John G.

Baylon, David M.

Galarza, Ruben E.

Hinds, Raynard O.

Lim, Jae S.

Reed, Eric C.

Sunshine, Lon E.

Wan, Wade

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Chapter 2. Advanced Telecommunications and Signal Processing ProgramAdvanced Telecommunications and Signal ProcessingProgramAcademic and Research StaffProfessor Jae S. LimVisiting Scientists and Research AffiliatesM. Carlos KennedyGraduate StudentsJohn G. Apostolopoulos, David M. Baylon, Rubenshine, Wade WanE. Galarza, Raynard O. Hinds, Eric C. Reed, Lon E. Sun-Technical and Support StaffCindy LeBlanc, Christopher R. O'Donnell, Denise M. Rossetti2.1 IntroductionThe present television system was designed nearly50 years ago. Since then, there have been significantdevelopments in technology, which are highly rele-vant to the television industries. For example,advances in the very-large-scale-integration (VLSI)technology and signal processing theories make itfeasible to incorporate frame-store memory andsophisticated signal processing capabilities in a tele-vision receiver at a reasonable cost.To exploit this new technology in developing futuretelevision systems, the Advanced TelevisionResearch Program (ATRP) was established at MIT in1983 by a consortium of U.S. companies.The major objectives of ATRP are:1. To develop the theoretical and empirical basisfor the improvement of existing television sys-tems, as well as for the design of future televi-sion systems.2. To educate students through television-relatedresearch and development and to motivatethem to undertake careers in television-relatedindustries.3. To facilitate continuing education of scientistsand engineers already working in the industry.4. To establish a resource center where problemsand proposals can be brought for discussionand detailed study.5. To transfer the technology developed from thisprogram to the television industries.The research areas of this program focused on anumber of issues related to digital television design.As a result of this effort, significant advances havealready been made; and these advances have beenincluded in the U.S. digital television standard. Spe-cifically, the ATRP group represented MIT in MIT'sparticipation in the Grand Alliance, this alliance con-sisted of MIT, AT&T, Zenith Electronics Corporation,General Instrument Corporation, David SarnoffResearch Center, Philips Laboratories, and ThomsonConsumer Electronics. The Grand Alliance digitaltelevision system served as the basis for the U.S.digital television (DTV) standard, which was formallyadopted by the U.S. Federal Communications Com-mission.In addition to research on issues related to thedesign of digital television system, our research pro-gram also includes research on (1) signal processingfor telecommunications applications and (2) speechenhancement.2.1.1 PatentsLim, J.S. "Method and Apparatus for Encoding,Decoding, and Compression of Audio-TypeData." Patent #5,625,746. April 29, 1997.Lim, J.S. "Encoding, Decoding and Compression ofAudio-Type Data Using Reference CoefficientsLocated Within a Band of Coefficients." Patent#5,640,486. June 17, 1997.333Chapter 2.Chapter 2. Advanced Telecommunications and Signal Processing Program2.2 Signal Processing for Signals withArbitrarily Shaped Regions ofSupportSponsorsAdvanced Telecommunications Research ProgramAT&T FellowshipProject StaffJohn G. ApostolopoulosMany applications today and in the near future willentail efficient processing of multidimensional (MD)signals with arbitrarily shaped (nonrectangular)regions of support. For example, most high level rep-resentations of images or video incorporate 2D or 3Dmodels which decompose the scene into arbitrarilyshaped objects or regions. Medical imaging oftenresults in 2D or 3D imagery where the relevant infor-mation is localized over an arbitrarily shaped region.Furthermore, many areas of scientific researchinvolve problems defined over arbitrarily shapeddomains. High quality and computationally efficientprocessing of these arbitrarily shaped signals isimportant for the success of these applications.Transform/subband representations form a basicbuilding block for many signal processing algorithmsand applications. Most of the effort has focused ondeveloping representations for infinite-length signals,with simple extensions to finite-length 1D and rectan-gular support 2D signals. However, the importantproblem of representing 2D or general MD signalswith arbitrarily shaped regions of support hasreceived relatively little attention. We have developeda novel framework for creating critically sampled per-fect reconstruction transform/subband representa-tions for discrete 1D, 2D, and general MD signalsdefined over arbitrarily shaped regions of support.Our method selects an appropriate subset of vectorsfrom an (easily obtained) basis for a larger (superset)signal space in order to form a basis for the arbitrarilyshaped signal. In particular, we have developed anumber of promising wavelet representations forarbitrary-length 1 D signals and arbitrarily shaped 2D/MD signals that provide high performance with lowcomplexity.2.2.1 PublicationsApostolopoulos, J.A., and J.S. Lim. "Transform/Sub-band Representation for Signals with ArbitrarilyShaped Regions of Support." Proceedings ofICASSP 97, Munich, Germany, April 21-24,1997, pp. 2097-2100.2.3 Source Multiplexing for Variable BitRate Video with Partial or CompleteInformationSponsorAdvanced Telecommunications Research ProgramProject StaffDavid M. BaylonVideo compression algorithms for fixed bandwidthsystems typically operate at fixed targeted compres-sion ratios. A problem with fixed bit rate systems isthat video quality can vary greatly within an imageand across an image sequence. In order to achievemore constant quality video, variable bit rate codingcan be performed, where bit allocation is allowed tovary more widely as the video statistics change.Although it may be inefficient to transmit a single vari-able rate encoded source over a constant rate chan-nel, it becomes more appropriate if several variablerate sources are combined to share a given fixedbandwidth. In source multiplexing, bit-rate fluctua-tions of each source are effectively averaged, makingthe aggregate bitstream more suitable for a constantrate channel. Applications for source multiplexinginclude video transmission over terrestrial or cablechannels, where it may be desirable to transmit sev-eral video programs simultaneously over a fixed ratechannel.Traditional video compression and video multiplexingsystems for bandwidth limited channels employcausal processing of the video data. This is neces-sary for delivery of real-time video programs. How-ever, many video programs such as movies are pre-recorded and can be pre-processed before perform-ing the actual compression and multiplexing fortransmission. By exploiting information about each ofthe entire video sequences before the compressionand multiplexing, better video quality can be deliv-ered compared to causal compression and multiplex-ing systems. The goal of this research is tocharacterize what gains in video quality can be334 RLE Progress Report Number 140Chapter 2. Advanced Telecommunications and Signal Processing Programachieved by having noncausal information about thevideo programs being compressed and multiplexed.This work focuses on MPEG-2 compression, and it isassumed that the video encoder and decoder buffersizes are constrained, and that the transmissionduration for a video program over a bandwidth limitedchannel is the same as the video program duration.Preliminary results with noncausal processing of asingle video program show improved and more con-stant video quality compared to causal processing.2.4 Speech EnhancementSponsorsGEM FellowshipU.S. Federal Bureau of InvestigationProject StaffRuben E. GalarzaThe problem of enhancing speech degraded by addi-tive background noise has received considerableattention over the years. Various techniques havebeen developed to solve this problem, each capitaliz-ing on specific characteristics or constraints. To date,model based enhancement systems (enhancementsystems based on parameter estimation) have pro-duced the best results in reconstructing speechdegraded by additive noise. However, these tech-niques are ultimately limited by the model in whichthey are based.In general, the underlying assumption of all modelbased algorithms for enhancing speech is that eachspeech segment is assumed stationary for a fixedwindow. This assumption is false, since the durationof stationarity varies for different classes of soundsand speakers. A viable solution is to find the desiredstationary regions before the model based enhance-ment takes place.Following this train of thought, an algorithm wasdeveloped for the segmentation of speech into(nearly) stationary regions by means of M-banddecomposition and adaptive windowing. Noisereduction is then achieved by applying a modifiedWiener filter based on selective linear prediction, tak-ing into consideration the local signal to noise ratio ofthe region being enhanced. The main purpose of thisresearch is to study alternatives to improve this tech-nique and make it more computationally efficient forreal- time applications.2.5 Real-Time Video on the InternetSponsorsAdvanced Telecommunications Research ProgramLucent Technologies FellowshipProject StaffRaynard O. HindsThe Internet has become sufficient at transmittingdata over packet-switched networks. This is becausedata has no inherent delay constraints and can han-dle the delay jitter that occurs due to variable queu-ing delays across the network as well as the excessdelay that occurs from retransmission of lost packets.This research has looked at transmitting real-timevideo over this same network. Real-time video cannot tolerate excessive delay. Packets arriving aftertheir scheduled playback point at the receiver arediscarded; however, video sequences are capable oftolerating loss. Block-based video coders which relyon motion compensated block prediction for moredata compression have been used to code videoover networks. With the resulting packet loss thatoccurs on congested networks, coding mode selec-tion for each macroblock is significant in determiningthe overall distortion on the decoded videosequence. A methodology for optimal mode selectionin the presence of potential macroblock loss wasdeveloped for a restricted set of video coders. For agiven channel erasure description and error conceal-ment method, macroblock modes are selected forblock-based video coders with zero-motion compen-sation to minimize the distortion for a given bit-rateconstraint. Future research must be done to find asolution when motion compensation is allowed.2.6 Digital Processing of UnderwaterImagesSponsorsAdvanced Telecommunications Research ProgramCharles S. Draper LaboratoryU.S. Navy - Office of Naval ResearchNDSEG Graduate FellowshipProject StaffEric C. ReedThis project focuses on compression of underwaterimages taken from an unmanned undersea vehicle(UUV) system. The channel that is available for com-335Chapter 2. Advanced Telecommunications and Signal Processing Programmunication between a UUV system and the remotelocation may support a bit-rate capacity as low as 10kbps. However, the video sequence of underwaterimages may have in the order of a few million pixels/sec at a resolution of 8 bits/pixel. Therefore the bit-rate reduction required for video transmission ofunderwater images is by a factor of several thou-sand. To achieve such a high rate of compression, avideo compression system must fully adapt to thecharacteristics of underwater images.Underwater images are often blurred and have lowcontrast because of low light illumination, scatteringof light, water turbulence, and sedimentation. In addi-tion, since a UUV system typically does not move ata very fast speed relative to the frame rate, the corre-lation that exists in the temporal domain is very high.We are exploring methods to exploit the temporalredundancy. For example, we are considering tem-poral subsampling of the source prior to encodingand then reconstructing the skipped frames at thedecoder by motion-compensated temporal interpola-tion. We are also considering global parametricmotion models which require negligible overhead buthave enough degree of freedom to describe the 2Dimage motion induced from the 3D motion of thecamera attached to the UUV.Furthermore, since an image is formed by recordingthe light reflected from an object that is illuminated bya light source attached to the UUV, an image can bemodeled as a product of illumination and reflectancecomponents. Since the illumination component isapproximately stationary over long periods of time, itmay represent redundant information and thereforeonly needs to be transmitted once over long periodsof time.The goal of this project is to compress the underwa-ter images to a bit rate of 10 kbps while preservingimage detail and overall video quality for a humanoperator to observe. This technology may have a sig-nificant impact on a variety of future underwaterapplications.2.6.1 PublicationReed E., and J.S. Lim. "Efficient Coding of DCTCoefficients by Joint Position-dependent Encod-ing." Proceedings of ICASSPR 1998.2.7 HDTV Transmission FormatConversion and the HDTV MigrationPathSponsorsAdvanced Telecommunications Research ProgramProject StaffLon E. SunshineThe current proposal for terrestrial HDTV broadcast-ing allows for several possible transmission formats.Because production and display formats may differ, itwill be necessary to convert between formats in aneffective way. A key to this process is the de-interlac-ing process. Since HDTV will presumably movetoward progressive display systems, it will be neces-sary to de-interlace nonprogressive source material.The research will consider topics relating to conver-sion among the six formats being proposed for theUS HDTV standard.As HDTV evolves, it is possible (and likely) that moretransmission formats will be allowed. Furthermore,additional bandwidth may be allocated for somechannels (terrestrial and/or cable). This research willconsider the issues related to the migration of HDTVto higher resolutions. Backward compatibility andimage compression and coding issues will beaddressed.2.8 Study on Migration to a HigherResolution Digital TelevisionSystemSponsorsAdvanced Telecommunications Research ProgramProject StaffWade WanHigh-definition television will begin broadcasting overthe next few years. The need to broadcast at higherresolutions than those currently allowed has alreadybeen recognized. A generally accepted resolutiongoal for terrestrial high-definition broadcasting ismore than 1000 lines with progressive scanning at 60frames per second within one single 6 MHz channel.Current transmission and compression technologiescannot support such a high-video resolution within a6 MHz channel.336 RLE Progress Report Number 140Chapter 2. Advanced Telecommunications and Signal Processing ProgramWe are currently investigating methods to displayvideo at the desired higher resolution formats usingvideo enhancement bits. This approach would con-sist of sending two sets of information within thebandwidth allocated for HDTV transmission. Stan-dard video bits would be transmitted at a lower reso-lution format that current technologies can support.An advanced HDTV receiver could receive the stan-dard video bits and then convert the video to a higherresolution format with the assistance of the videoenhancement bits. Standard HDTV receivers couldignore the enhancement bits and display video at thelower resolution format.This backward-compatible approach is highly desir-able tonot make standard HDTV receivers obsolete.Previous research in our laboratory has shown thatthis approach is feasible for transmitting 1080 lineinterlaced scanned images at 60 fields per secondand using the enhancement bits to assist the deinter-lacer performed at the receiver. We will be investigat-ing the use of different transmission formats tomigrate toward higher resolution formats using thisenhancement data approach. For example, progres-sively scanned video may be transmitted with 720lines at 60 frames per second and then spatiallyupsampled at the receiver. This research will allow usto determine the best transmission format and signalprocessing schemes for optimum picture quality.337338 RLE Progress Report Number 140

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