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Where technology & law meet: Open Access research on data security & its regulation ...

Strathprints makes available Open Access scholarly outputs exploring both the technical aspects of computer security, but also the regulation of existing or emerging technologies. A research specialism of the Department of Computer & Information Sciences (CIS) is computer security. Researchers explore issues surrounding web intrusion detection techniques, malware characteristics, textual steganography and trusted systems. Digital forensics and cyber crime are also a focus.

Meanwhile, the School of Law and its Centre for Internet Law & Policy undertake studies on Internet governance. An important component of this work is consideration of privacy and data protection questions and the increasing focus on cybercrime and 'cyberterrorism'.

Explore the Open Access research by CIS on computer security or the School of Law's work on law, technology and regulation. Or explore all of Strathclyde's Open Access research...

Compressive image sampling with side information

Stankovic, V. and Stankovic, L. and Cheng, S. (2009) Compressive image sampling with side information. In: Image processing (ICIP) 2009. IEEE, New York, pp. 3037-3040. ISBN 9781424456536

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Abstract

Compressive sampling is a novel framework that exploits sparsity of a signal in a transform domain to perform sampling below the Nyquist rate. In this paper, we apply compressive sampling to reduce the sampling rate of images/video. The key idea is to exploit the intra- and inter-frame correlation to improve signal recovery algorithms. The image is split into non-overlapping blocks of fixed size, which are independently compressively sampled exploiting sparsity of natural scenes in the discrete cosine transform (DCT) domain. At the decoder, each block is recovered using useful information extracted from the recovery of a neighboring block. In the case of video, a previous frame is used to help recovery of consecutive frames. The iterative algorithm for signal recovery with side information that extends the standard orthogonal matching pursuit (OMP) algorithm is employed. Simulation results are given for magnetic resonance imaging (MRI) and video sequences to illustrate advantages of the proposed solution compared to the case when side information is not used