• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.10
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• pp.1961-1966
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• 2016

Compressive sensing has proved that a signal can be restored from less samples than the Nyquist rate. Reducing the required data rate is essential for a variety of fields including compression, transmission, and storage. It has been made lots of attempt to apply the compressive sensing theory into data intensive fields, such as image processing which needs to cover 4K and 8K pictures. In this paper, an image acquisition algorithm based on compressive sensing is proposed. It combines DCT, which can compact the energy of a image into a few coefficients, and the Noiselet transform, which is incoherent with DCT. The DCT coefficients represent the coarse structure of the images while the Noiselet information holds the fine details. Performance experiments with several images show that the proposed image acquisition algorithm not only outperforms the previous results, but also improves the reconstruction quality faster as the number of measurements increases.