Pingfan Song

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We study the problem of measurement matrix design for Compressive Sensing (CS) when the encoder has access to side information, a signal analogous to the signal of interest. In particular, we propose to incorporate this extra information into the signal acquisition stage via a new design for the measurement matrix. The goal is to reduce the number of(More)
Real-world data processing problems often involve multiple data modalities, e.g., panchromatic and multispectral images, positron emission tomography (PET) and magnetic resonance imaging (MRI) images. As these modalities capture information associated with the same phenomenon, they must necessarily be correlated, although the precise relation is rarely(More)
In many applications, performing spectrum sensing after sampling at the Nyquist rate is inefficient because the signals of interest contain only a small number of significant frequencies relative to the band limit, although the locations of the frequencies may not be known a priori. For this type of signal, we focus on improve Random Demodulation, a novel(More)
Real-world data processing problems often involve various image modalities associated with a certain scene, including RGB images, infrared images or multispectral images. The fact that different image modalities often share diverse attributes, such as certain edges, textures and other structure primitives, represents an opportunity to enhance various image(More)
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