Abstract
AbstractMeasuring digital image quality is of importance in numerous applied research fields, such as image acquisition, image processing or image reconstruction. Subjective evaluation, i.e. assessment by human beings, is often too time‐consuming, expensive and inconsistent in complicated tasks such as medical imaging. In order to better understand the relation between objective image quality assessment measures, we compare a selection in an experimental setup. It is well known that L2 error estimation, i.e. computing the mean squared error (MSE) between two images, does not correspond well to the perceptual evaluation by the human visual system. Here, we illustrate on the example of MRI data the interaction of the MSE with the signal to noise ratio (SNR), the variance and subjective evaluation. We use random coverings of the space of orthogonal projections for coil combination to enable a comprehensive correlation analysis.
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