The field of signal and image processing encompasses the theory and practice of algorithms and hardware that convert signals produced by artificial or natural means into a form useful for a specific purpose. The signals might be speech, audio, images, video, sensor data, telemetry, electrocardiograms, or seismic data, among others; possible purposes include transmission, display, storage, interpretation, classification, segmentation, or diagnosis. Faculty members in this field span the areas of digital signal processing, statistical signal processing, image/video compression, analysis & processing, speech processing, music information retrieval and computer audition.
Current research in digital signal processing includes robust and low complexity filter design, signal reconstruction, filter bank theory, and wavelets. In statistical signal processing, faculty interests include adaptive filtering, learning algorithms for neural networks, spectrum estimation and modeling, and sensor array processing with applications in sonar and radar. Image processing work is in restoration, compression, quality evaluation, computer vision, and medical imaging. Speech processing research includes modeling, compression, and recognition. Video compression, analysis,and processing projects include error concealment technique for 3D compressed video, automated and distributed crowd analytics, stereo-to-autostereoscopic 3D video conversion, virtual and augmented reality. Also, faculty members are actively involved in the research and design of special purpose electronic and optoelectronic hardware for efficient implementation of signal, image and video processing algorithms.