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 noisy or under sampled imaging measurements, the instructions executable by the at least one processing device to: adapt a transform model to a first set of image patches of a first set of images containing at least a first image, to model the first set of image patches as sparse in a transform domain while allowing deviation from perfect sparsity; reconstruct a second image by minimizing an optimization objective comprising a transform-based regularizer that employs the transform model, and a data fidelity term formed using the imaging measurements; and store the second image in the computer-readable medium, the second image displayable on a display device.