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Compressive image sampling with side information

Stankovic, V. and Stankovic, L. and Cheng, S. (2009) Compressive image sampling with side information. [Proceedings Paper]

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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

Item type: Proceedings Paper
ID code: 39696
Keywords: image processing, image reconstruction, compressive image sampling, side information, data mining, video compression , matching pursuit algorithms, magnetic resonance imaging, layout, iterative decoding, iterative algorithms, image sampling, image coding , discrete cosine transforms, Electrical engineering. Electronics Nuclear engineering
Subjects: Technology > Electrical engineering. Electronics Nuclear engineering
Department: Faculty of Engineering > Electronic and Electrical Engineering
Related URLs:
    Depositing user: Pure Administrator
    Date Deposited: 14 May 2012 15:01
    Last modified: 17 Jul 2013 14:07
    URI: http://strathprints.strath.ac.uk/id/eprint/39696

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