Signal processing algorithms for applications in communication systems

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The field of digital signal processing (DSP) has experienced an explosive growth during the past couple of decades. The DSP techniques have become integral parts of the products and services that we need or encounter in our daily lives. The research efforts of the applicant during the past five years have led to some very concrete results that have been shared with international scientific community, both from academia and industry, and have given rise to new ideas and directions that need to be further investigated. The overall objective of the proposed research is to develop efficient algorithms and to establish the underlying mathematical foundations for reliable processing of speech, image and video signals, and for their efficient software and hardware implementation for multimedia communication applications. The distortion of images by additive or multiplicative noise is common during their acquisition, compression, storage, transmission and reproduction. Presence of the noise makes the automatic interpretation of image data very difficult. Voice activity detection, pitch estimation of noise-corrupted speech, and identification and modeling of noisy speech systems are vital for reliable design of speech communication systems. Emerging communication and information networks deal with high volumes of digital speech, image and video signals and with their transmission through over-congested communication channels. Fundamental to these activities are the signal compression, and pre- and post-processing of such signals. Efforts will be put to reach solutions to these problems through design and implementation of DSP algorithms that are cost effective and are superior in performance. Discrete transforms are essential to signal processing tasks. To this end, new transforms exploiting more efficiently the intrinsic properties of signals will be investigated. Fast and efficient techniques for computing these and the existing transforms will be undertaken. Research efforts will also be directed towards efficient software and VLSI implementations of the algorithms developed in this proposal.