Array Communications & Array Processing
Array Communications and Array Processing have evolved into a well-established research area moving from old diversity systems, conventional direction nulling and phased-arrays to space-time communications, advanced superresolution direction finding algorithms and superresolution beamformers. The idea of combining Arrays with Communication Systems is recent and has the potential of providing more powerful wireless communication systems where both space and time information is exploited.
Biomedical Image and Signal Processing
Image and Signal Processing has a lot to offer to Biomedical sciences: Biomedical data analysis may be used to make explicit information that is implicit in the data, thus help us understand better how the human body works and also help the clinicians with diagnosis and visualisation of their data. The Group has active projects concerning the analysis of EEG and MEG data, 3D MRI data related to cancer research, microarray data concerning gene expression, and work combining computer graphics with image processing technologies for plastic surgery planning.
With the realisation of new generations of network technologies, the integration and interoperation of multiple heterogeneous networks supporting mobile services and user facilities will be of great importance. The Communication Networks Team is concerned with research leading to the development of techniques to enhance the responsiveness of new technologies and systems when facing dynamic traffic changes, a variety of user requirements and the deployment of new services.
Computational imaging refers to a set of imaging techniques that combine the design of the hardware layer (e.g., optical components, illumination, sensors, and devices) with signal processing techniques in order to go beyond physical limitations of traditional optical systems and achieve novel imaging capabilities that one could not with traditional imaging methods. In computational imaging, computation plays an integral role in the image formation process, for this reason, this research area is intimately related to sampling theory and aspects of sparse sampling.
In collaboration with the bio-engineering department, the group is active in using computational imaging methods to enhance to quality and resolution of two-photon microscope images of the brain, it also develops methods to enhance the capabilities of digital cameras in smartphones by leveraging the computational power of modern mobile phones and finally is investigating the use of computational imaging techniques for application in the art and humanity sectors.
Computer vision is closely associated with image processing and patter recognition. In the simplest terms, computer vision aspires to make computers reason on the content of digital images. The Group has active research projects on cognitive vision, that combines machine learning and computer vision, networks of cameras that cooperate to track moving objects, 3D reconstruction of objects for face modelling and recognition, and on more fundamental aspects of how the human visual system works.
Image Processing encompasses a variety of techniques applied to digital images in the broadest sense of the word: optical images, hyperspectral images captured by satellites orbiting the Earth, 3D seismic images of the crust of the Earth, 3D tomographic images of the human body, as well as video sequences. The Group has active research on image fusion, enhancement, restoration, texture and shape analysis, object recognition, invariant feature construction, colour analysis etc.
The highly successful introduction and rapid growth of mobile telephone networks has re-emphasised the need for the efficient use of the limited bandwidth that is available. The activity of the mobile communication research group is, in one way or another, concerned with the research into techniques for improving the efficiency of bandwidth utilisation, and with techniques for improving the reliability of communication over fading channels.
Remote Sensing and the Environment
With the recent climatic changes, the environment is at the forefront of public concern. Earth observation data coming from satellites orbiting the Earth may be combined with ground collected data, map information and other sources to help us monitor the state of the environment, create hazard maps for possible natural disasters, forecast and monitor events like landslides and floods, as well as manage resources and recommend actions. The group has a lot of experience in such research projects.
Sparse Signal Processing and Compressed Sensing
The notion of sparsity, namely the idea that the essential information contained in a signal can be represented with a small number of significant components, is widespread in signal processing and data analysis in general. Great progress for example in image compression and enhancement has been obtained by modeling signals as sparse in an appropriate domain, typically the wavelet domain. The understanding that sparsity can be used to drive directly the information acquisition process is instead much more recent.
The group has years of experience in sparse signal representation, sampling based on sparsity models and applications in sparse inference, compression, super-resolution and tracking. Current research projects are in the area of dictionary learning for sparse representation, construction of sampling matrices/operators, finite rate of innovation sampling and a wide range of applications from estimation of diffusion fields, to imaging and neuroscience as well as channel estimation and sensing.
The Speech Processing group has years of experience in noise cancellation for speech enhancement, speaker verification using HMM methods and voice source parameters, as well as multi-rate stereophonic acoustic echo cancellation. We also research in speech coding, epoch detection for speaker verification and time segmentation for acoustic echo cancellation.
Stochastic Signals and Filters
The team research effort is directed towards the development of design techniques for fixed and adaptive parameter digital filters. Moreover, it looks into implementation issues on a range of platforms (FPGA, DSP Chips, ASICs) and their application in a wide range of stochastic signal processing problems.