Patent ID: 9734601
Date: 2017-08-15
CPC Classifications: G06T

Claim:
1. A system comprising: at least one processing device; non-transitory computer-readable medium storing instructions executable by the at least one processing device to employ transform learning as a regularizer for reconstructing an image from limited or corrupted imaging measurements, to generate a reconstructed image, wherein the limited or corrupted imaging measurements include a component that is a function of at least two pixels of the reconstructed image, wherein ones of the at least two pixels reside in different image patches of a plurality of image patches of the reconstructed image, and the instructions to cause the at least one processing device to: wherein x is the reconstructed image, y are the imaging measurements, f (x, y) is the data fidelity term that includes interactions between data from the different image patches, λ is a regularization strength parameter, and J(x) is the transform-model-based image regularizer of the reconstructed image, which is obtained as an approximate minimum solution to a transform learning minimization problem that comprises: store the reconstructed image in the computer-readable medium, the reconstructed image displayable on a display device.