Howtosignalprocessing
- What is meant by compressed sensing?
- Why is compressed sensing important?
- What is compressed sensing in image processing?
- What is compressed sensing in MRI?
What is meant by compressed sensing?
Compressed sensing (also known as compressive sensing, compressive sampling, or sparse sampling) is a signal processing technique for efficiently acquiring and reconstructing a signal, by finding solutions to underdetermined linear systems.
Why is compressed sensing important?
Compressive sensing possesses several advantages, such as the much smaller need for sensory devices, much less memory storage, higher data transmission rate, many times less power consumption. Due to all these advantages, compressive sensing has been used in a wide range of applications.
What is compressed sensing in image processing?
Compressed sensing (CS) is an image acquisition method, where only few random measurements are taken instead of taking all the necessary samples as suggested by Nyquist sampling theorem. It is one of the most active research areas in the past decade.
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.
