Education and Research in the Center for Signal

Education and Research in the Center for Signal and Image Processing http: //www. eedsp. gatech. edu/

2 CSIP Summary • • Our Ph. D. graduates have impact worldwide in DSP education and research Distinguished faculty – – • • • 17 faculty (7 IEEE Fellows) Co-authors of over 25 books on DSP Over 80 current Ph. D. students Located on third floor of GCATT building 250 14 th St. , NW Support from Georgia Research Alliance has provided outstanding well equipped labs. Center for Signal and Image Processing

Beowulf Cluster 26 dual processors 1 Gbyte memories Center for Signal and Image Processing

CSIP Faculty • Yucel Altunbasak • Chin Lee • David V. Anderson • Vijay K. Madisetti • Thomas P. Barnwell • Francois Malassenet • Mark A. Clements • James H. Mc. Clellan • Faramarz Fekri • Monson H. Hayes • Joel R. Jackson • Fred Juang • Aaron Lanterman • Russell M. Mersereau • Ronald W. Schafer • Douglas B. Williams • G. Tong Zhou Center for Signal and Image Processing

Past and Present Funding • Industry: Texas Instruments, Intel, BAE Systems, Hewlett-Packard, Mathworks, National Semiconductor, Analog Devices, Lucent, Harris, Hughes, Prentice-Hall • Federal: NSF, U. S. Army, DARPA, ONR, NASA, MPO • State: Georgia Research Alliance • Private Foundation: John and Mary Franklin Foundation • Total Funding: Current funding from government and industry totals about $6. 5 M Center for Signal and Image Processing

Industrial Partnership Examples • Texas Instruments Leadership Univ. Program – Members with MIT and Rice U. – Seven projects - 7 faculty and 7 Ph. D. students – Wireless video, CFA interpolation, speech coding, speech recognition, chaotic systems, face recognition, MIMO communication systems • Hewlett Packard Laboratories – Four faculty and six students – Focus on PDAs: low-power analog front-ends, structured audio, applications in education. Also, 3 D video for video conferencing, – HP Labs researcher in residence Center for Signal and Image Processing

Linearization of RF Power Amplifiers G. Tong Zhou, J. Stevenson Kenney • Power amplifiers (PAs) are inherently nonlinear. – Desire: high efficiency PAs, leading to low cost. – Downside of high efficiency: high nonlinearity. – Nonlinearity causes: (1) high bit error rate; (2) adjacent channel interference: must satisfy FCC. • DSP-based predistortion linearization. – Challenging issue: memory nonlinear effects in high power amplifiers (e. g. , base station PAs). • Indirect Learning Architecture adapts to changing characteristics • RF TESTBED Center for Signal and Image Processing

Indirect Learning Architecture Advantage: No need to model or identify the PA. Center for Signal and Image Processing

8 -Tone Test Result • 8 -tone, 1. 2 MHz signal, Siemens CGY 0819 dual-band PA • Purple: w/o PD; green: w/ memoryless PD (K=7); cyan: w/ memory polynomial PD (K=7, Q=10) • 35 d. B of spectral regrowth suppression w/ memory polynomial PD Center for Signal and Image Processing

Video Resolution Enhancement Y. Altunbasak and R. Mersereau • Future broadcasting will be all digital. • High definition displays will dominate the market. • However, most programming is expected to be in SDTV format. There is a clear need and technical opportunity to design systems to enhance the quality of the SDTV signal so that it matches the quality and capabilities of high definition displays. Center for Signal and Image Processing

Applications - Digital Cameras Subsequent multiple pictures (JPEG format) Reconstructed high-resolution picture Also applicable to high-quality printing from video sources such as DVD players, set-top boxes, TV sets, software MPEG players and camcorders. Requires a resolution enhancing print driver. Center for Signal and Image Processing

Face Recognition Monson H. Hayes Major problem is lighting and pose variations. Center for Signal and Image Processing

Results and Next Step • We have developed a new face recognition system based on a segmented linear subspace model – Robust to varying illuminations and tolerant to different poses, – Has recognition accuracy equaling or exceeding (>99%) other state-of-the-art systems, and – Has a fraction of the complexity. • Next Step: Face Recognition from Video – Face detection (patent awarded). – Pose detection (find best frontal view). – Face recognition (robust to varying illuminations, poses, facial expressions). • The Intriguing Question – How can we incorporate the multitude of images that are extracted from video to enhance the recognition system? Center for Signal and Image Processing

Finite Field Wavelet Transforms F. Fekri and D. Williams Goal: Establishment of a new research field that brings together researchers from signal processing, error control coding, data security and multicarrier signaling systems. Finite Field Wavelets Error Control Coding OFDM Modulation Security coding Center for Signal and Image Processing

New Research Directions in Data Security LL row-wise LH HL HH column-wise LL LH HL HH New Research Directions in Error Control Coding Center for Signal and Image Processing

Passive Radar Systems Aaron Lanterman Exploit “illuminators of opportunity” such as commercial TV and FM radio broadcasts for covert operation Target Tracking Positions Velocities Passive Radar System Signature Prediction via Computational EM Radar Cross Section Radar Imaging Target Classification Target Library Center for Signal and Image Processing

Imaging With 100. 0 on Your FM Dial Target Shape Formatted Raw Data Image Formed Via Processing F-22 Falcon-100 VFY-218 Center for Signal and Image Processing

Detection of Obscured Targets Jim Mc. Clellan & Waymond Scott • Landmines – No single sensor has proven capable of reliable detection across many types of “targets” – Can multiple sensors be used cooperatively to produce a system with robust performance? • A three sensor experiment – Electromagnetic Induction (EMI) Sensor – Ground Penetrating Radar (GPR) Sensor – Seismic Sensor • Multimodal processing – Imaging & Inversion – Cooperative Fusion of multiple sensors Center for Signal and Image Processing

EMI Sensor and GPR Sensor Physical Properties of Target Permittivity Contrast EMI Sensor: 0. 6 - 60 k. Hz Low Conductivity (Dielectric) High Conductivity (Metal) Mechanical Contrast EMI No Weak Yes No GPR Yes Yes* No Seismic No No No Yes GPR: 500 MHz – 8 GHz Tx 4. 5” Rx Center for Signal and Image Processing

Seismic Sensor: Surface Waves Man-made items often resonate Center for Signal and Image Processing

Comparison of EMI, GPR and Seismic Responses: VS-1. 6, 6. 5 cm deep EMI Seismic GPR x depth y t Center for Signal and Image Processing

Comparison of EMI, GPR & Seismic Responses Uncrushed Aluminum Can, 2 cm deep EMI GPR Seismic x depth y t Center for Signal and Image Processing

Cooperative Analog/Digital Signal Processing D. Anderson and P. Hasler • Target: Complex signal processing functionality with extremely low power • Approach: Perform substantial amounts of the processing in programmable analog VLSI Real world (analog) DSP Processor A/D Convertor Computer (digital) Specialized A/D Real world (analog) ASP IC A/D DSP Processor Computer (digital) Center for Signal and Image Processing

Cooperative Analog/Digital Signal Processing • Advantages of CADSP: – Better problem “fit” – Orders of magnitude improvement in power consumption / efficiency – Simpler A/D converter requirements, – Smaller size. • Current Applications Include: – – – Audio noise suppression Audio source localization / beam-steering Focal plane image / video processing Speech Recognition Field Programmable Analog Processor Arrays Center for Signal and Image Processing

Digital Media Asset Management Mark Clements • Sam Nunn Archives: Cooperative Effort between CSIP, IMTC, GT and Emory Libraries. • Fast searching of audio based on phonetic content. Typical speed of search: 72, 000 x real time (20 hours of content searched in 1 elapsed second). – Basis for startup company Fast-Talk which has received over $10 M venture funding. • New results demonstrate rapid searching of music by lyrics and melodies using same approach. Center for Signal and Image Processing

Current Research Areas - I • Robust automatic speech recognition • New architectures for speech recognition • High-quality low-bit-rate speech coding for voice over IP networks • Noise and reverberation removal • Music analysis and synthesis • Compressed-domain processing of audio • Multi-scale sinusoidal modeling • Microphone array processing • Blind separation of speech signals • Chaos in wireless communication systems • Space-time coding and OFDM • Compensation for selective fading effects Center for Signal and Image Processing

Current Research Areas - II • Target tracking in video • Automated measurement and modeling of behavior in biological systems • “Intelligent Environments” • Automatic storage/retrieval of speech and audio • Audio-visual speech recognition • Speech-driven facial animation • Video streaming with error concealment and MDC • Graphics streaming for the Internet • Buried mine detection using GPR, seismic & EMI • Target Tracking in sensor networks • Hyperspectral imaging and target classification • SAR imaging Center for Signal and Image Processing

Current Research Areas - III • Automated analysis of video • Video indexing for a smart VCR • Image interpolation for digital color cameras • Super-resolution of video • Image-based graphical rendering • Segmentation of cardiac MRI images • DSP for hand-held communication devices • Finite field wavelet transforms and applications to error control coding and cryptography • Application of multimedia processing in education • Compensation of nonlinear power amps. • Face Recognition • Video compression Center for Signal and Image Processing

Summary • The premier academic program in the country in the signal processing field is in the Georgia Tech School of Electrical and Computer Engineering. • We have many outstanding graduate students. – Internships – Long-term contributors • We have lots of outstanding technology waiting to be developed. • We have a demonstrated capability to work with industry. • Contact me if you want to come for a visit. jim. mcclellan@ece. gatech. edu Center for Signal and Image Processing