منابع مشابه
Blind compressive sensing dynamic MRI with sparse dictionaries
Each row shows few spatial frames and the image time profile. We observe a similar behavior as seen in fig.1. k-t FOCUSS showed some temporal blur (see yellow arrow in (b)). BCS had better temporal fidelity but suffered from noisy artifacts (see arrows in (c) due to learning noisy patterns. Sparse BCS resulted in reconstructions with reduced noise like artifacts without compromising on the spat...
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Random sampling in compressive sensing (CS) enables the compression of large amounts of input signals in an efficient manner, which is useful for many applications. CS reconstructs the compressed signals exactly with overwhelming probability when incoming data can be sparsely represented with a fixed number of components, which is one of the drawbacks of CS frameworks because the signal sparsit...
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In this paper, we summarize our recent results on simultaneous compressive sensing reconstruction and blind deconvolution of images, captured by a compressive imaging system introducing degradation of the captured scene by an unknown point spread function. © 2013 Optical Society of America OCIS codes: 100.3020, 100.1455, 100.3190
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ژورنال
عنوان ژورنال: IEEE Transactions on Medical Imaging
سال: 2013
ISSN: 0278-0062,1558-254X
DOI: 10.1109/tmi.2013.2255133