Applicability of compressed sensing / compressive sensing

1. Where is compressed sensing used?
2. What is compressed sensing used for?
3. What is compressive sensing theory?
4. What is compressed sensing in MRI?

Where is compressed sensing used?

In a wide range of applications, the compressive sensing can be applied, like data mining [6,7], text processing [8], signal processing [9,10], agriculture on-board data processing [11,12], image enhancement [13,14], acoustic OFDM [15], medical image processing [16–18], image adaptation [19] Electrocardiogram ...

What is compressed sensing used for?

Compressed sensing can be used to improve image reconstruction in holography by increasing the number of voxels one can infer from a single hologram. It is also used for image retrieval from undersampled measurements in optical and millimeter-wave holography.

What is compressive sensing theory?

The compressive sensing theory states that the signal can be reconstructed using just a small set of randomly acquired samples if it has a sparse (concise) representation in certain transform domain.

What is compressed sensing in MRI?

Compressed sensing (CS) is a method for accelerating MRI acquisition by acquiring less data through undersampling of k-space. This has the potential to mitigate the time-intensiveness of MRI.