Compressed sensing or compressive sensing is a new concept in
signal processing where one measures a small number of non-adaptive
linear combinations of the signal. These measurements are usually
much smaller than the number of samples that define the signal.
From these small numbers of measurements, the signal is then
reconstructed by non-linear procedure. Compressed sensing has
recently emerged as a powerful tool for efficiently processing data
in non-traditional ways. In this book, we highlight some of the key
mathematical insights underlying sparse representation and
compressed sensing and illustrate the role of these theories in
classical vision, imaging and biometrics problems.
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