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The field of SIgnal and Image Processing encompasses the development and implementation of algorithms and means to analyze and extract information from signals obtained from observing a phenomenon. The original signals can be a variety of types arising in a multitude of applications, including speech, audio, camera images, video, remote sensor data, telemetry, and MRI. Possible processing goals for such signals include transmission, display, storage, interpretation, classification, segmentation, or diagnosis.
Research thrusts currently include:
- Biological and Medical Signal Processing
Faculty: Karl, Nawab
The creation of new ways to probe biological media is providing researchers with unprecedented data concerning a range of biological phenomenon, ranging from the molecular to the clinical. With these new sources of information come new challenges. The objective of this thrust is to develop new methods of signal and image processing allowing quantitation and robust qualification based on such data. Topics include image reconstruction, image restoration, sampling and interpolation, imaging in scattering media, image setmentation and registration, data fusion, deformable methods, to name a few. Probing modalities include optical and fluorescence microscopy, computed tomography, ultrasound, MRI, dynamic PET & SPECT. Applications include: molecular imaging, brain imaging; dynamic imaging; interventional imaging.
- Statistical Signal Processing
Faculty: Castanon, Karl, Saligrama, Ishwar
The area of statistical signal processing focuses on the robust extraction of information in the face of uncertain data and models. Typically one is given a probabilistic description for an input signal and a model for a system that changes or distorts the signal. The resulting noisy observation is combined with these models to design algorithms for optimal processing. Fundamental issues include the nature of the basic probabilistic signal description, the model of the distorting system, the probabilistic description of the output signal given that of the input signal and the system, and the design of processing paradigms that are both appropriate and yet lead to tractable algorithms. Applications areas include communications, control, estimation, and decision making. Current research interests involve solution of inverse problems, decision making, recognition processing, and sensor networks.
- Digital Signal Processing
Faculty: Nawab
Digital signal processing is concerned with the design and application of generic (i.e. application-independent) methods for representing and manipulating digital signals. DSP algorithms and architectures are often designed from the perspective of computational efficiency in order to permit their practical use in real-time and/or low-power applications such as telephony, compact-disc players, speech recognizers, and automotive suspension systems.
- Image Processing
Faculty: Bystrom, Karl, Konrad
Image processing is a rapidly evolving field with growing applications in both professional and consumer markets. While computer-aided tomography (CAT), extensively used in life sciences, is an example of application in the professional market, digital photography is an example of a very successful application in the consumer market. Fundamental issues studied in this thrust cover problems related to visual perception, sampling and quantization of visual data, image restoration and enhancement, image segmentation, and image recognition, as well as image transmission and storage (image compression, watermarking, authentication, etc.)
- Auditory Signal Processing
Faculty: Nawab
Auditory Signal Processing is concerned with the the digital representation and manipulation of microphone data. The methods utilized may come from digital signal procesing, statistical signal processing, and/or the study of the human auditory system. Applications of interest include speech restoration, speech enhancement, speaker separation, auditory scene analysis, and automatic music transcription.
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